Candidate fact checking method and system

ABSTRACT

A fact checking system is able to verify the correctness of information and/or characterize information by comparing the information with one or more sources. The fact checking system automatically monitors, processes, fact checks information and indicates a status of the information. Fact checking results are able to be validated by re-fact checking the fact check results.

CROSS-REFERENCE TO RELATED APPLICATION(S)

The present application is a continuation of U.S. patent applicationSer. No. 14/804,187 filed Jul. 20, 2015; which is a continuation of U.S.patent application Ser. No. 13/763,831 filed Feb. 11, 2013, now U.S.Pat. No. 9,087,048; which is a continuation-in-part of U.S. patentapplication Ser. No. 13/565,013 filed Aug. 2, 2012; which is acontinuation-in-part of U.S. patent application Ser. No. 13/528,563filed Jun. 20, 2012, now U.S. Pat. No. 8,321,295; which is acontinuation of U.S. patent application Ser. No. 13/448,991 filed Apr.17, 2012, now U.S. Pat. No. 8,229,795; which is a continuation of U.S.patent application Ser. No. 13/287,804 filed Nov. 2, 2011, now U.S. Pat.No. 8,185,448; which claims priority to U.S. Provisional PatentApplication No. 61/495,776 filed Jun. 10, 2011, all of which are herebyincorporated by reference in their entireties for all purposes. Thepresent application also claims the benefit of U.S. Provisional PatentApplication No. 61/736,181 filed Dec. 12, 2012, which is herebyincorporated by reference in its entirety for all purposes, to which aclaim of priority is made by U.S. patent application Ser. No. 13/763,831filed Feb. 11, 2013.

FIELD OF THE INVENTION

The present invention relates to the field of information analysis. Morespecifically, the present invention relates to the field ofautomatically verifying the factual correctness of a statement.

BACKGROUND OF THE INVENTION

Information is easily dispersed through the Internet, television andmany other outlets. One major problem is that the information dispersedis often not correct. Although there are fact checking websitesavailable online, these websites check facts in a slow manner; typicallynot truly providing a fact check response for several hours or evendays.

SUMMARY OF THE INVENTION

A fact checking system verifies the correctness of information and/orcharacterizes the information by comparing the information with one ormore sources. The fact checking system automatically monitors,processes, fact checks information and indicates a status of theinformation.

The fact checking system includes many embodiments, some of which aresummarized herein. The fact checking system is able to be used toprovide supplemental information, for example, information regarding acommunication, information about a person or other entity,advertisements, opposing advertisements, information about a user,information about an item, media analysis, commercial analysis, biasclassification, a follow-up question for a host, arguments and opposingarguments, and information based on the importance to a user.

The fact checking system is able to be implemented using rated sources,classified sources, a recognition system, learning, contextdetermination, auto-correction, parallel computing and/or many otherfeatures.

The fact checking system will provide users with vastly increasedknowledge, limit the dissemination of misleading or incorrectinformation, provide increased revenue streams for content providers,increase advertising opportunities, and support many other advantages.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a flowchart of a method of implementing fact checkingaccording to some embodiments of the present invention.

FIG. 2 illustrates a block diagram of various implementations of factchecking according to some embodiments.

FIG. 3 illustrates exemplary screenshots of various implementations offact checking according to some embodiments.

FIG. 4 illustrates a block diagram of an exemplary computing deviceconfigured to implement fact checking according to some embodiments.

FIG. 5 illustrates a diagram of a network of devices configured toimplement fact checking according to some embodiments.

FIG. 6 illustrates exemplary implementations according to someembodiments.

FIG. 7 illustrates exemplary source ordering according to someembodiments.

FIG. 8 illustrates an example of providing supplemental informationbased on information from a television where the supplementalinformation is displayed on a user's mobile device according to someembodiments.

FIG. 9 illustrates a flowchart of a method of providing additional orsupplemental information according to some embodiments.

FIG. 10 illustrates an exemplary table of arguments and counterarguments according to some embodiments.

FIG. 11 illustrates an exemplary table of brands according to someembodiments.

FIG. 12 illustrates an exemplary data structure implementing selectionsand advertising according to some embodiments.

FIG. 13 illustrates an exemplary listing of headlines with an importancerating according to some embodiments.

FIG. 14 illustrates a flowchart of a method of determining an importanceof information according to some embodiments.

FIG. 15 illustrates a flowchart of a method of presenting a viewingschedule according to some embodiments.

FIG. 16 illustrates an exemplary viewing schedule according to someembodiments.

FIG. 17 illustrates a flowchart of a method of performing televisionanalysis according to some embodiments.

FIG. 18 illustrates an exemplary user interface for receiving searchinformation for television analysis according to some embodiments.

FIG. 19 illustrates an exemplary screenshot of an alert using televisionanalysis according to some embodiments.

FIG. 20 illustrates an exemplary screenshot of search results accordingto some embodiments.

FIG. 21 illustrates a flowchart of a method of using opposing argumentsby an opposing entity according to some embodiments.

FIG. 22 illustrates an exemplary user interface for receiving userselections for information analysis according to some embodiments.

FIG. 23 illustrates an exemplary user interface for receiving opposingargument selections according to some embodiments.

FIG. 24 illustrates a flowchart of a method of implementing a factchecker fantasy game according to some embodiments.

FIG. 25 illustrates a flowchart of a method of presenting a single clickpurchase implementation according to some embodiments.

FIG. 26 illustrates an exemplary single click purchase implementation onmultiple devices according to some embodiments.

FIG. 27 illustrates a flowchart of a method of implementing a candidatefact checker according to some embodiments.

FIG. 28 illustrates a flowchart of a method of implementing acontroversy tracker according to some embodiments.

FIG. 29 illustrates a flowchart of a method of performing analysis of auser according to some embodiments.

FIG. 30 illustrates a flowchart of a method of utilizing fact checkingto determine search engine results according to some embodiments.

FIG. 31 illustrates a flowchart of a method of utilizing cloud computingfor fact checking and providing supplemental information according tosome embodiments.

FIG. 32 illustrates a diagram of fact checking glasses according to someembodiments.

FIG. 33 illustrates an exemplary chart comparing the accuracy of severalentities according to some embodiments.

FIG. 34 illustrates a flowchart of a method of fact checking the factchecking system according to some embodiments.

FIG. 35 illustrates a flowchart of a method of rating sources accordingto some embodiments.

FIG. 36 illustrates a vehicle with fact checking capabilities accordingto some embodiments.

FIG. 37 illustrates a flowchart of a method of using fact checking withautofill information according to some embodiments.

FIG. 38 illustrates a flowchart of a method of fact checking andsummarizing according to some embodiments.

FIG. 39 illustrates a flowchart of a method of detecting manipulation ofsources according to some embodiments.

FIG. 40 illustrates a flowchart of a method of implementing a checklistof campaign promises according to some embodiments.

FIG. 41 illustrates an exemplary voting fact checking app according tosome embodiments.

FIG. 42 illustrates an exemplary table of a candidate comparisonaccording to some embodiments.

FIG. 43 illustrates a flowchart of a method of voting fact checkingaccording to some embodiments.

FIG. 44 illustrates a flowchart of a method of voting fact checkingaccording to some embodiments.

FIG. 45 illustrates an exemplary table of news coverage analysisaccording to some embodiments.

FIG. 46 illustrates a flowchart of a method of fact checking contactsaccording to some embodiments.

FIG. 47 illustrates a diagram of a graphical user interface of factchecked contacts according to some embodiments.

FIG. 48 illustrates a block diagram of furniture used in conjunctionwith fact checking

FIG. 49 illustrates an exemplary changing of a window size according tosome embodiments.

FIG. 50 illustrates a flowchart of a method of myth clarificationaccording to some embodiments.

FIG. 51 illustrates a flowchart of a method of implementing aninteractive fact checking system according to some embodiments.

FIG. 52 illustrates a diagram of a smart phone display with a list oficons representing detected characterizations.

FIG. 53 illustrates a flowchart of a method of determining if arespondent answers a question according to some embodiments.

FIG. 54 illustrates a flowchart of a method of providing contentappropriate for children based on content directed at adults accordingto some embodiments.

FIG. 55 illustrates a flowchart of a method of classifying informationby political party according to some embodiments.

FIG. 56 illustrates a flowchart of a method of detecting andhighlighting loaded words according to some embodiments.

FIG. 57 illustrates a flowchart of a method of detecting accusations ofbias by one entity against another according to some embodiments.

FIG. 58 illustrates a flowchart of a method of using a search engine incooperation with social network information and fact checkinginformation according to some embodiments.

FIG. 59 illustrates a flowchart of a method of fact checking a messageboard according to some embodiments.

FIG. 60 illustrates a block diagram of fact checking interactions with amessage board according to some embodiments.

FIG. 61 illustrates a screen shot of an exemplary message boardimplementing fact checking according to some embodiments.

FIG. 62 illustrates a screen shot of an exemplary message boardimplementing fact checking before allowing a user to post according tosome embodiments.

FIG. 63 illustrates a flowchart of a method of fact checking productreviews according to some embodiments.

FIG. 64 illustrates a flowchart of a method of monitoring for criticismof the fact checking system according to some embodiments.

FIG. 65 illustrates a flowchart of a method of calculating the amount oftime or number of times an entity or topic is discussed according tosome embodiments.

FIG. 66 illustrates a flowchart of a method of implementing selectivefact checking according to some embodiments.

FIG. 67 illustrates a flowchart of a method of implementing factchecking using multiple thresholds according to some embodiments.

FIG. 68 illustrates a block diagram of various implementations of factchecking according to some embodiments.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

A fact checking system verifies the correctness or accuracy ofinformation by comparing the information with one or more sources.Although the phrase “fact checking” is used, any sort of informationanalysis is to be understood (e.g. determining a phrase is “spin” orsarcasm).

Monitoring

The fact checking system monitors any information including, but notlimited to, text, video, audio, verbal communications or any other formof communication. Communications include, but are not limited to email,word processing documents, Twitter (tweets), message boards, web pagesincluding, but not limited to, Facebook® postings and web logs, anycomputing device communication, telephone calls, television audio, videoor text, other text, radio, television broadcasts/shows, radiobroadcasts, face-to-face conversations, VoIP calls (e.g. Skype™), videoconferencing, live speech and any other communication that is able to beanalyzed. In some embodiments, monitoring includes recording, scanningor any other type of monitoring. In some embodiments, monitoring alsoincludes capturing and/or transmitting the data. In some embodiments,monitoring includes determining if a portion of the information is factcheckable.

Processing

To perform fact checking, the monitored information is processedincluding, but not limited to, transmitted, converted, parsed,formatted, analyzed and reconfigured using context determination and/orany other processing. For example, voice data is converted to text,screen text is converted to usable text, graphics are converted to ausable form of data, or any other data conversion is able to beimplemented to enable fact checking. For some types of monitoredinformation, little, if any, processing is performed. For example, textwhich is already properly formatted is able to be fact checked withoutany conversion. In another example, when comparing audio to searchableaudio records conversion may not be needed. In some embodiments,processing also includes capturing and/or transmitting the data.Formatting is able to include changing the order of words deletingunnecessary words and/or any other formatting to enable the informationto be searched.

Verification/Fact Checking

The information including, but not limited to, phrases, segments,numbers, words, comments, values, graphics or any other data is analyzedor verified using the fact checking system. In some embodiments, aphrase is first located or determined, and then it is analyzed. Theverification or fact checking process compares the data to be verifiedwith data from one or more sources. In some embodiments, the sources areweb pages on the Internet, one or more databases, one or more datastores and/or any other source. In some embodiments, the source is apersonal source including, but not limited to, an online log or diary.

In some embodiments, the data verification or fact checking is astraight text comparison, and in some embodiments, anotherimplementation including, but not limited to, natural language,context/contextual comparison or intelligent comparison is used. In someembodiments, a combination of search implementations is used.

An example of a straight text comparison is comparing the phrase, “Texasis the largest state” with text to find “Texas is the largest state.”When the text is not found because Alaska is the largest state, a resultof false is returned. An example of a context comparison is: “Texas isthe largest state” where a list of states by size is found, and Texas islocated in the list; when Texas is not #1, a result of false isreturned, or the location in the list is returned, e.g. #2. In anotherexample of context comparison: “Texas is the largest state,” the landmass of Texas is compared with land masses of the other 49 states, andsince Texas does not have the largest land mass, the result is false. Anexample of an intelligent comparison is: X criticizes Y because Y had anaffair, then the intelligent comparison locates a story that indicates Xhad an affair two years ago. An indication of hypocrisy by X ispresented.

In some embodiments, previously checked facts are stored (e.g. in adatabase on a server) to prevent the perpetration of a false statementor story, or other characterization. In some embodiments, the facts arefirst checked manually or automatically which is able to occur inreal-time or non-real-time, but then when a repeat occurrence happens,the results of that fact check occurs in real-time. For example, a storythat Candidate X is a communist is presented by one commentator. Thestory is fact checked, and the result of the fact check (e.g. not true)is stored, including the original comment and any context related. Then,when another commentator or anyone else says, “Candidate X is acommunist,” the fact checker uses the previously stored result toimmediately inform a viewer/user that the story is not true. Thus,commentators and others will not bother perpetuating a false story asthey will not only be proven wrong immediately but will also damagetheir credibility.

In some embodiments, the sources are rated using a rating system so thatsources that provide false or inaccurate information are rated as pooror unreliable and/or are not used, and sources that rarely providemisinformation are rated as reliable and are used and/or given moreweight than others. For example, if a source's rating falls or is belowa threshold, that source is not used in fact checking. In someembodiments, users are able to designate the threshold. For example, auser specifies to fact check using only sources with an “A” rating orhigher. In some embodiments, sources' ratings are available or shown tousers. In some embodiments, users are able to rate sources. In someembodiments, sources are rated based on previous fact checking resultsto determine computer-generated ratings. For example, if a source isproven wrong by comparing the data with other sources or the resultswith other sources' results, that source would be rated as poor. Forfurther example, Source X indicates that Z is true, but twenty otherreliable sources indicate that Z is false. Such a result would affectSource X's reliability rating negatively. Examples of very reliablesources include a dictionary and an encyclopedia. An example of apotentially very unreliable source includes a biased, opinion web logthat fabricates stories. In some embodiments, an impartial group ororganization rates the sources, or any other method of rating thesources is used. In some embodiments, sources are reviewed by an agency(e.g. an independent rating agency) to obtain a reliability rating. Insome embodiments, a combination of user ratings, computer ratings and/orother ratings is implemented. In some embodiments, there are separateclasses of ratings or reviews including, but not limited to, generalusers, experts, friends, co-workers, news organizations or any othergroups. The rating system is able to be numeric including, but notlimited to, 1-10, by grades including, but not limited to A-F or anyother rating or grading system. Furthermore, the rating system is ableto be incorporated into a mathematical equation to provide higherquality results. For example, if a statement is being verified, and twodifferent sets of results are found such that one set of resultsverifies the statement as fact and the other set verifies the statementas fiction, the one from the higher rated sources is selected. A sampleequation is:

Source Result Value=Number of Sources*Average Rating of Sources, wherethe search path with highest Source Result Value determines theverification result. For example, “Person X is running for president,”results in 10 sources with an average rating of 9 (where 1 isuntrustworthy and 10 is very trustworthy) saying “True,” and 20 sourceswith an average rating of 2 saying “False,” the result would be “True”since (10*9)=90 is greater than (20*2)=40. Another sample equation is:Source Result Value=(Source Rating1+Source Rating2+ . . . SourceRatingn)/number of sources.

In some embodiments, the sources are classified in one or moreclassifications including, but not limited to, comedy, opinion, fact,fiction, and/or political. Any other classifications, groupings,sub-classifications, and/or sub-groupings are possible. In someembodiments, sources are rated in political terms including, but notlimited to, independent, ultra-liberal, leaning left, neutral/moderate,leaning right, ultra-conservative, green, and libertarian.

In some embodiments, a user is able to customize which sources are usedand/or not used. For example, if a user believes Source Z providesinaccurate information, the user is able to mark that source so that itis not used. In some embodiments, sources are clustered, so that a useris able to select a cluster instead of individual sources. For example,a user is able to select to use all dictionary and encyclopedicreferences. In some embodiments, a user is able to select sources basedon characteristics including, but not limited to, a politicalcharacterization (e.g. conservative). Any other user selection orexclusion of sources is possible.

In some embodiments, a phrase to be fact checked may not have an exactanswer, the answer may not be known at the time, or the fact checkingsystem may not be able to find the answer. If this occurs, a “bestguess” is able to be selected and presented. In some embodiments, eachresult from a source that is checked is able to include a resultaccuracy rating. For example, if a fact to be checked is, “the U.S. has50 states,” many sources should return a 100% accuracy rating for theresult since it is easily searched for and determined within thesources. However, if a fact to be checked is not easily determined, theresults may be less than 100% accurate and could therefore be labeled asa “best guess” including a confidence/accuracy/certainty percentage,instead of a fact.

In some embodiments, for example, where the facts are not certain, acollective determination system is used. For example, a determinationthat 40 sources (e.g. sites) agree with the statement and 5 disagree,allows the user to make a judgment call and look further into thestatement.

In some embodiments, where a subjective statement is made or asked,ratings, objective information, and/or subjective information is locatedto determine the accuracy of the statement or question. For example, ifa person says, “Star Wars is better than Star Trek,” ratings informationgiving Star Wars an 8.5 and Star Trek and 8.0 would verify the validityof the statement, and the fact checker would return the statement“True.” The ratings information is able to be any ratings informationincluding, but not limited to, user ratings, critic ratings, otherratings or a combination thereof. In some embodiments, if an opinion isdetected (e.g. by recognizing, “in my opinion,” “I think” or anotheropinion phrase), the statement is not ruled as valid or invalid, butsupporting information is able to be detected and presented (e.g. 10sites agree with your opinion and 5 disagree). In some embodiments, ifan opinion without basis/justification is detected, an indication of“unfounded opinion” is indicated or the basis is presented. In someembodiments, pros and cons of each are provided so that the user is ableto make the determination of which is better. In some embodiments, whena user submits a subjective item, one or more results are presented thatanswer the subjective item. For example, if a user searches using asearch engine for “the best restaurant in San Francisco,” a singlerestaurant is presented which has the highest rating for restaurants inSan Francisco. In some embodiments, since there are several ratingagencies/sites, multiple restaurants are presented, and a descriptionsuch as “highest rated by X” is presented next to each result. Forexample, Restaurant X is highest rated by source A, Restaurant Y ishighest rated by source B and Restaurant Z is highest rated by source C.In some embodiments, all of the rating agencies/sites are compared, anda single entity is presented. For example, if there are 10 sites thatrate songs, and 8 agree that Song J is the best ever, while 2 agree thatSong L is the best ever, Song J is presented as the best song ever. Insome embodiments, users are able to select how they want the resultspresented including, one ultimate result, a list of results, a graph ofresults, and/or any other presentation.

In some embodiments, context determination is used such that the contextof the comment is checked in determining the validity of the comment.For example, if someone says, “he wasted billions of dollars,” the “he”is determined based on additional context surrounding the statement. Inanother example, the question is also analyzed to determine if theresponse is valid. For instance, if a question asks, “Did you receiveany money illegally?,” and a respondent answers, “I have not beenconvicted of a crime,” that comment is able to be flagged as “spin,”“unresponsive,” “questionable” or the like, since technically the answerto the question is true, but the point of the question has not reallybeen answered. Other forms of context checking are able to beimplemented as well to provide more information to the viewer. In someembodiments, when “spin,” a nonresponsive response or any sort ofquestionable response is detected, a host is notified, so that he isable to press the issue. For example, a television show host asks aguest if the guest has ever “cheated on his taxes,” and the guestresponds with, “I have never been convicted of tax fraud.” A yellowlight is displayed to signal the host to ask the question in a differentmanner or further press the issue to try to get to the truth. Asdescribed herein, in some embodiments, an additional question isautomatically presented (e.g. on a teleprompter or in his earpiece), sothat the host does not have to formulate the additional question. Insome embodiments, a follow-up question is presented to the host afterevery response by the guest. In some embodiments, the question is basedon the guest's answer.

Context is able to be used in many ways to find an answer. For example,if Person A says Person B is biased, there may not be an exact statementto be found that says, “Person B is biased.” However, using context,biased quotes, pictures, stories, audio, video or other data may befound from Person B which would indicate he is biased. Additionally,when there may be a gray area such as someone being biased, both sidesare able to be found and presented for the viewer to determine thetruth. For example, audio with Person B denigrating a specific groupwould indicate bias, but video of that same person helping that specificgroup would indicate non-bias or a change of view.

In some embodiments, hyperbole, sarcasm, comedy and other linguisticstyles are checked and/or detected, and the information is indicated assuch. Detection occurs using any contextual qualities including, but notlimited to, the tone, the channel/station/type of website (e.g. a newschannel), and/or type of person (e.g. comedian).

In some embodiments, causation is analyzed and fact checked. Forexample, if Z makes the statements, “A is Russian, Russia in the pastwas communist, therefore A is a communist,” an indication that thecausation is weak is presented. Weights of causation are able to beindicated including, but not limited to, weak causation, strongcausation or a number rating including, but not limited to, 1 through10. In some embodiments, causation is able to be analyzed by determininglinks between items, and the greater the number of links and/or theseverity of the links, the greater the causation. Where causation isdifficult to analyze and/or establish, an alert questioning causation isindicated. For example, if a commentator makes the statement that pricesof goods went up in the under President Z, if there is insufficient datato indicate that the prices went up because of actions President Z took,an indication of “questionable causation” is able to be presented. Insome embodiments, causation (or lack thereof) is determined by logicalflaws or incorrectness. For example, if a commentator makes the claimthat President Z harmed businesses by lowering taxes, an indication of“poor causation” is able to be made since it is logically inconsistentfor lowering taxes to harm businesses. In some embodiments, sourcessupporting and/or contradicting the information are displayed. In someembodiments, a list or another description is displayed indicating otherpossible causes for the result. For example, if a commentator says theeconomy is in trouble because of the President, a list of other possiblecauses could be displayed such as Congress, a credit collapse, andothers, including percentages next to each indicating percentages basedon previous polling.

In some embodiments, when the data verification or fact checking occurs,one or more dedicated sources are used. In some embodiments, one or morenon-dedicated sources are used. In some embodiments, a combination ofdedicated and non-dedicated sources is used. In some embodiments, thereliability of the data verification depends on the number of sourcesused. For example, if a story has 5 independent sources that verify thestory, then that would be considered and denoted more reliable than astory with 1 source. The reliability of the sources is also able toaffect the reliability of the story. For example, although 5 sourcesverify a story, if the sources are all poorly rated sources in terms ofreliability, then that story may be considered less reliable than astory that has 1 very reliable source. In some embodiments, animplementation is used to determine if the same story/article is usedmore than once as a source. For example, if there is only one source foran article but the same story is posted on ten different websites, insome embodiments, that repetition is recognized and only counts as oneverification source.

In some embodiments, a user performs a check of the automatic fact checkresults.

In some embodiments, checks are performed to ensure sources or sourcedata are not stale, or that stale sources or source data are not usedwhen fact checking. For example, if the statement, “X is running forPresident” is made regarding the 2016 election, and several sources havedata that show X ran for President in 2000, that data is ignored sinceit does not prove that X is running in the 2016 election. Checking forstale sources and source data is able to be done by comparing a creationdate of the data or other characteristics or landmarks of the sources ordata or any other manner.

In some embodiments, via social networking, contacts' sources' searchresults or other related information is used when performing a user'ssearch. For example, a user fact checks the “Tiger is the best golfer,”and a contact (e.g. friend) had already done this fact check. Theresults from that fact check are given to this user. This is able toimprove search speed and accuracy.

Indicating Status

After fact checking is performed, an indication or alert is used toindicate/inform/alert a user of a status of the information including,but not limited to, correct/true/valid or incorrect/false/invalid. Inaddition to correct and incorrect, other gray area indicators arepossible including, but not limited to, “unknown,” “depending on thecircumstances” or “close to the truth.” Additionally, any other statusindicators are possible. The indicators are able to be any indicatorsincluding, but not limited to, lights, sounds, highlighting, text, atext bubble, a scrolling text, color gradient, headnotes/footnotes, aniconic or graphical representation (e.g. a meter, Pinocchio's nose orthumbs up/down), a video or video clip, music, other visual or audioindicators, a projection, a hologram, a tactile indicator including, butnot limited to, vibrations, an olfactory indicator, a Tweet, an email, apage, a phone call, or any combination thereof. For example, text isable to be highlighted or the text color is able to change based on thevalidity of the text. For example, as a user types, the true statementsare displayed in green, the questionable statements are displayed inyellow and the false statements are displayed in red. Similarly, when acommentator speaks on a television program, true statements aredisplayed in a first color and false statements are displayed in asecond color. Additional colors or shades of color or brightness ofcolors are able to be used to indicate other items including, but notlimited to, hyperbole, opinions, and other items. In some embodiments,sources to the verification data are provided (e.g. using hyperlinks orcitations). In some embodiments, the text itself includes a hyperlink.The source enables the user to verify the statement himself, forexample, by reviewing an original source for an article. In someembodiments, a phrase itself is not affected or labeled, but additionalinformation is provided in close proximity. For example, if a politicianon a talk show says, “the President raised the deficit by $1 T thisyear,” the fact checking system presents data showing the deficit fromlast year and this year, so that users are able to compare what thepolitician said and what an independent source said. In someembodiments, indicating includes transmitting and/or broadcasting theindication to one or more devices (e.g. televisions).

In some embodiments, the fact checking system is implemented such thatresponses, validity determinations and/or indications are available inreal-time or near real-time. By real-time, it is meant instantaneously,for example, such that when a politician makes a comment on a politicalshow, within a second or a few seconds, the comment is fact checked, andan indication of the validity of the comment is presented. Furthermore,since the monitoring, processing, fact checking and indicating are allable to be performed automatically without user intervention, real-timealso means faster than having a human perform the search and presentingresults. Depending on the implementation, in some embodiments, theindication is presented in at most 1 second, at most several seconds(e.g. at most 5 seconds), at most a minute, at most several minutes orby the end of a show. In some embodiments, the time amount (e.g. at most1 second) begins once a user pauses in typing, once a phrase has beencommunicated, once a phrase has been determined, at the end of asentence, once an item is flagged, or another point in a sequence. Forexample, a commentator makes the comment, “Z is running for President.”As soon as that phrase is detected, the fact checker checks the fact,returns a result and displays an indication based on the result in lessthan 1 second—clearly much faster than a human performing a search,analyzing the search results and then typing a result to be displayed ona screen.

FIG. 1 illustrates a flowchart of a method of implementing fact checkingaccording to some embodiments of the present invention.

In the step 100, information is monitored. In some embodiments, allinformation is monitored; in some embodiments, only some information ismonitored; or in some embodiments, only explicitly selected informationis monitored. In some embodiments, although all information ismonitored, only some information (e.g. information deemed to befact-based) is utilized for the fact check analysis. Monitoring is ableto be implemented in any manner including, but not limited to, storingor recording the information, transmitting the information, and anyother method of monitoring. The information to be monitored is anyinformation including, but not limited to, television audio, video ortext, other text, radio, television broadcasts/shows, radio broadcasts,word processing data and/or documents, email, Twitter (tweets), messageboards, web pages including, but not limited to, Facebook® postings andweb logs, any computing device communication, telephone calls,face-to-face conversations, VoIP calls (e.g. Skype™), videoconferencing, live speech and any other information. In someembodiments, monitoring includes, but is not limited to, observing,tracking, collecting, scanning, following, surveying and/or overseeing.

In the step 102, the information is processed. In some embodiments,processing includes converting the information into a searchable format.During or after the information is monitored, the information isconverted into a searchable format. Processing is able to include manyaspects including, but not limited to, converting audio into text,formatting, parsing data, determining context and/or any other aspectthat enables the information to be fact checked. Parsing, for example,includes separating a long speech into separate phrases that are eachseparately fact checked. For example, a speech may include 100 differentfacts that should be separately fact checked. In some embodiments, thestep 102 is able to be skipped if processing is not necessary (e.g. textin word processor may not need to be processed).

In a more specific example of processing, broadcast information isconverted into searchable information (e.g. audio is converted intosearchable text), and then the searchable information is parsed intofact checkable portions (e.g. segments of the searchable text; severalword phrases). Parsing is able to be implemented in any mannerincluding, but not limited to, based on sentence structure (e.g.subject/verb determination), based on punctuation including, but notlimited to, end punctuation of each sentence (e.g. period, questionmark, exclamation point), based on search results and/or any othermanner. In some embodiments, processing includes, but is not limited to,calculating, computing, storing, recognition, speaker recognition,language (word, phrase, sentence, other) recognition, labeling, and/orcharacterizing.

In the step 104, the information is fact checked. Fact checking includescomparing the information to one or more sources of information todetermine the validity, accuracy, quality, character and/or type of theinformation. In some embodiments, the comparison is a straight word forword text comparison. In some embodiments, the comparison is a contextcomparison. In some embodiments, an intelligent comparison isimplemented to perform the fact check. Any method of analyzing thesource information and/or comparing the information to the sourceinformation to analyze and/or characterizing the information is able tobe implemented. An example implementation of fact checking includessearching (e.g. a search engine's search), parsing the results orsearching through the results of the search, comparing the results withthe information to be checked using one or more of the comparisons (e.g.straight text, context or intelligent) and retrieving results based onthe comparison. The results are able to be any type including, but notlimited to, binary, Boolean (True/False), text, numerical or any otherformat. In some embodiments, determining context and/or other aspects ofconverting could be implemented in the step 104. In some embodiments,the sources are rated and/or weighted. Although the phrase “factchecking” is used, any sort of information analysis is to be understood(e.g. determining a phrase is sarcasm).

In the step 106, a status of the information is indicated. The status isindicated in any manner including, but not limited to, transmittingand/or displaying text, highlighting, underlining, color effects, avisual or audible alert or alarm, a graphical representation, and/or anyother indication. The meaning of the status is able to be any meaningincluding, but not limited to, correct, incorrect, valid, true, false,invalid, opinion, hyperbole, sarcasm, hypocritical, comedy, unknown,questionable, suspicious, need more information, deceptive, and/or anyother status. The status is also able to include other informationincluding, but not limited to, statistics, citations and/or quotes.Indicating the status of the information is also able to includeproviding additional information related to the fact checkedinformation. In some embodiments, indicating includes pointing out,showing, displaying, recommending, playing, presenting, announcing,arguing, convincing, signaling, asserting, persuading, demonstrating,denoting, expressing, hinting, illustrating, implying, tagging,labeling, characterizing, and/or revealing.

In some embodiments, fewer or more steps are implemented. Furthermore,in some embodiments, the order of the steps is modified. In someembodiments, the steps are performed on the same device, and in someembodiments, one or more of the steps, or parts of the steps, areseparately performed and/or performed on separate devices.

EXAMPLE 1

A news channel broadcasts a show with political commentary. The showallows a host and guests to discuss various political issues. As thehost and guests make comments, their comments are monitored, convertedfrom speech to text and automatically fact checked using online datasources. Based on the results of the fact check, a status of thecomments is shown. For example, if the guests respond with factuallyaccurate statements, no alert is displayed. However, when a guest orhost makes an untrue statement, an alert is displayed at the bottom ofthe screen including a quote of the incorrect statement and a correctionto the statement. If a guest “spins” a comment, the fact checker is ableto determine “spin” and indicate “spin” for the comment and provide datathat explains why it is spin. This ensures the guests provide valid dataand arguments, as well as maintains the integrity of the show.

EXAMPLE 2

A user is typing a report using a word processor. As the user is typing,the word processor monitors the information being input. Depending onthe format of the information, the information may not need to beconverted. The information, such as segments of the report, is factchecked. For example, a user is typing a report on the history of NewJersey and types, “Newark is the capital of New Jersey.” The factchecker would compare this segment with an online source such asWikipedia.org and determine that Trenton is the capital of New Jersey.As a result, the word processor would strikethrough “Newark” and next toit, insert Trenton, underlined. Any other means of indicating that theinformation is wrong is able to be used. In some embodiments,supplemental information and/or citation information is provided. Forexample, regarding the capital city, information such as Trenton becamethe capital in 1790, and the state flower is the Common Violet. In someembodiments, the fact checker is used as a citation finder. For example,if a user types in a statement, regardless of whether it is correct, theuser is able to select the text and click “cite finder” where the factchecker provides sources that verify the statement. The “cite finder” isnot limited to word processing applications and is able to be applied inany implementation.

EXAMPLE 3

A user posting information to his Facebook® page types commentaryregarding his favorite golfer, and says, “I can't believe Tiger came ineighth this week.” Using additional data such as knowing when thecommentary was written and that the user is an avid golf fan, aftermonitoring this information, converting the information including addingthe context of Tiger Woods (the famous golfer), at the Masters, in 2011,the fact checker is then able to compare this information with theresults of that specific tournament for that specific golfer. Then, ablurb with a citation is able to be posted on the user's Facebook® pageto indicate that Tiger actually finished fourth, or the user is informedso that he is able to correct the page himself.

EXAMPLE 4

A user searches using a search engine by inputting “Alaska is thelargest state.” The search engine provides a response of True and alsodisplays one or more links to the sources that support the result. Inanother example using the search engine, a user searches using thephrase, “Magic Johnson is taller than Michael Jordan.” The search enginedetermines that Magic Johnson is 6′9″ and Michael Jordan is 6′6″ andthen compares the heights with a mathematical operator to provide theresult of True. In some embodiments, the heights of each are displayed,and in some embodiments, one or more cites providing the informationused in the comparison are displayed.

FIG. 2 illustrates a block diagram of various implementations of factchecking according to some embodiments. As described herein, somespecific implementations are shown including, but not limited to, a wordprocessing component 200 for incorporation with a word processingapplication, an advertising component 202 for advertising, an entityvalidity rating component 204 for rating entities, a source ratingcomponent 206 for rating sources, a flagging component 208 for flaggingitems, a voice/facial/biometric recognition component 210 forrecognizing entities, a self-checking component 212 for checking a user,a learning component 214 for learning, an auto-correction component 216for implementing auto-correction, a search engine component 218 forimplementing a search engine fact checker, an audio/video/text component220 for fact checking audio, video, text and any other information, atranslator component 222 for translation-fact checking, a text component224 for fact checking an email, instant message, text messages, tweetsor other text communications, an item determination component 226 fordetermining an item, a media analysis component 228 for analyzing mediaincluding but not limited to, television and radio, a re-broadcastcomponent 230 for applying fact checking analysis to re-broadcastedinformation, a supplemental information component 232 for providingsupplemental information to content, an action component 234 for takingan action against an entity based on the fact checking, an opposingarguments component 236 for providing opposing arguments to content, aparallel component 238 for implementing parallel monitoring, processing,fact checking and/or indicating, an importance rating component 240 fordetermining the importance of content, and a medical fact checkercomponent 242 for fact checking medical information. The variousimplementations shown are not meant to be limiting in any way and aremerely examples of some of the possible implementations.

FIG. 3 illustrates exemplary screenshots of various implementations offact checking according to some embodiments.

Screenshot 300 shows a word processing display where a user typed astatement, the statement has been fact checked, and a notificationappears with a suggestion to correct the incorrect statement. Although abubble with the correction is shown, any form of indicating an errorand/or correction is possible including, but not limited to,underlining, strikethrough, highlighting, an icon, and/or an audiblealert. When there are multiple ways of correcting a statement, a user isable to be given options as described herein.

Screenshot 302 shows a television screen where a commentator is makingstatements. Since the commentator made a false statement, text isdisplayed at the bottom of the screen indicating the statement is falseand providing a correction of the false statement.

Screenshot 304 shows multiple forms of rating speakers on a televisionbroadcast. Statistics for the guest speaker in the window are shownbelow the window indicating the number of true statements he has madeand the number of false statements he has made. A rating is displayedunder the host of +10 which, for example, is a positive rating of +10 ona −10 to +10 truthfulness scale. These ratings enable users to determinehow trustworthy the speaker is based on past results.

Screenshot 306 shows a smart phone which monitored a user's comments andinformed him that he misspoke by saying the U.S. has 51 states.

Screenshot 308 shows a search engine search and result. In the example,the user searches for the fact, “Texas is the largest state.” The resultpresented is “False,” a correction is shown, and citations (links) ofsupporting websites or other sources are shown. In another the example,the user searches for the fact, “Alaska is the largest state.” Theresult presented is “True” and citations (links) of supporting websitesor other sources are shown. The displayed results are able to vary fromsimple (e.g. merely presenting True or False) to more detailed (e.g.presenting True or False, providing a correction if false, providingspecific information, and providing citations).

The various implementations illustrated in FIG. 3 are not meant to belimiting in any way and are merely examples of some of the possibleimplementations.

FIG. 4 illustrates a block diagram of an exemplary computing device 400configured to implement the fact checking method according to someembodiments. The computing device 400 is able to be used to acquire,store, compute, process, communicate and/or display informationincluding, but not limited to, text, images, videos and audio. In someexamples, the computing device 400 is able to be used to monitorinformation, process the information, fact check the information and/orindicate a status of the information. In general, a hardware structuresuitable for implementing the computing device 400 includes a networkinterface 402, a memory 404, a processor 406, I/O device(s) 408, a bus410 and a storage device 412. The choice of processor is not critical aslong as a suitable processor with sufficient speed is chosen. The memory404 is able to be any conventional computer memory known in the art. Thestorage device 412 is able to include a hard drive, CDROM, CDRW, DVD,DVDRW, flash memory card, solid state drive or any other storage device.The computing device 400 is able to include one or more networkinterfaces 402. An example of a network interface includes a networkcard connected to an Ethernet or other type of LAN. The I/O device(s)408 are able to include one or more of the following: keyboard, mouse,monitor, display, printer, modem, touchscreen, touchpad,speaker/microphone, voice input device, button interface, hand-waving,body-motion capture, touchless 3D input, joystick, remote control,brain-computer interface/direct neural interface/brain-machineinterface, and other devices. In some embodiments, the hardwarestructure includes multiple processors and other hardware to performparallel processing. Fact checking application(s) 430 used to performthe monitoring, converting, fact checking and indicating are likely tobe stored in the storage device 412 and memory 404 and processed asapplications are typically processed. More or less components shown inFIG. 4 are able to be included in the computing device 400. In someembodiments, fact checking hardware 420 is included. Although thecomputing device 400 in FIG. 4 includes applications 430 and hardware420 for implementing the fact checking, the fact checking method is ableto be implemented on a computing device in hardware, firmware, softwareor any combination thereof. For example, in some embodiments, the factchecking applications 430 are programmed in a memory and executed usinga processor. In another example, in some embodiments, the fact checkinghardware 420 is programmed hardware logic including gates specificallydesigned to implement the method.

In some embodiments, the fact checking application(s) 430 includeseveral applications and/or modules. Modules include a monitoring modulefor monitoring information, a processing module for processing (e.g.converting) information, a fact checking module for fact checkinginformation and an indication module for indicating a status of theinformation. In some embodiments, modules include one or moresub-modules as well. In some embodiments, fewer or additional modulesare able to be included. In some embodiments, the applications and/orthe modules are located on different devices. For example, a deviceperforms monitoring, converting and fact checking but the indicating isperformed on a different device, or in another example, the monitoringand converting occurs on a first device, the fact checking occurs on asecond device and the indicating occurs on a third device. Anyconfiguration of where the applications/modules are located is able tobe implemented such that the fact checking system is executed.

Examples of suitable computing devices include, but are not limited to apersonal computer, a laptop computer, a computer workstation, a server,a mainframe computer, a handheld computer, a personal digital assistant,a pager, a telephone, a fax machine, a cellular/mobile telephone, asmart appliance, a gaming console, a digital camera, a digitalcamcorder, a camera phone, a smart phone/device (e.g. a Droid® or aniPhone®), an iPod®, a tablet (e.g. an iPad®), a video player, ane-reader (e.g. Kindle™), a DVD writer/player, a Blu-ray® writer/player,a television, a copy machine, a scanner, a car stereo, a stereo, asatellite, a DVR (e.g. TiVo®), a home entertainment system or any othersuitable computing device.

FIG. 5 illustrates a network of devices configured to implement factchecking according to some embodiments. The network of devices 500 isable to include any number of devices and any various devices including,but not limited to, a computing device (e.g. a tablet) 502, a television504, a smart device 506 (e.g. a smart phone) and a source 508 (e.g. adatabase) coupled through a network 510 (e.g. the Internet). The sourcedevice 508 is able to be any device containing a source including, butnot limited to, a searchable database, web pages, transcripts,statistics, historical information, or any other information or devicethat provides information. The network 510 is able to any network ornetworks including, but not limited to, the Internet, an intranet, aLAN/WAN/MAN, wireless, wired, Ethernet, satellite, a combination ofnetworks, or any other implementation of communicating. The devices areable to communicate with each other through the network 510 or directlyto each other. One or more of the devices is able to be an end user, amedia organization, a company and/or another entity. In someembodiments, peer-to-peer sourcing is implemented. For example, thesource of the data to be compared with is not on a localized source butis found on peer sources.

For example, a news company uses its computers to monitor and processinformation presented on its broadcast. The processed information isthen fact checked with one or more sources (on site and/or external),and then the results are presented to the user's home device such as atelevision. The monitoring, processing, fact checking and presenting areall able to occur locally at the news company, externally by anotherentity, or parts occur locally and parts occur externally. In a modifiedexample, the results are sent to and presented to a user on hercomputer, smart phone or tablet while she is watching television.

In another example, when a user is watching television, the user's smartphone monitors and processes information from the television and sendsthe information to be fact checked, and then the results are presentedon the user's smart phone.

In another example, when a user is watching television, the user'scomputing device monitors and processes information from the televisionand sends the information to be fact checked, and then the results arepresented on the user's computing device.

In another example, when a user is watching television, the user's smartphone monitors and processes information from the television and sendsthe information to be fact checked, and then the results are sent fromthe user's smart phone to the television to be presented.

Any combination of devices performing the fact checking system ispossible.

Implementations Advertising

In some embodiments, advertising is incorporated with the fact checkingsystem. For example, a fact checking result includes, “This fact checkis brought to you by: Company X.” In some embodiments, the advertisingis related to the item being checked or the result of the fact check.For example, if the fact to be checked is “California is the mostpopulated state,” an advertisement about California is presented. Insome embodiments, the advertising is based on other information insteadof or in addition to the fact to be checked including, but not limitedto, a user's age, sex, location, occupation, industry of the fact,location of a subject, or any other information. In some embodiments,personal networking information is used including, but not limited to,Facebook® information. In some embodiments, coupons are presented withthe fact checking. For example, if a fact to be checked is whether “IceCream Z is gluten-free,” a coupon for Brand Z ice cream is presented tothe user. Another example is pay per click or click-through money-makingAny other implementation of making money using the fact checking systemis able to be implemented. FIG. 6 illustrates exemplary implementationsincluding an advertisement 600. Additional advertising implementationsare described herein, for example, in the Supplemental Informationsection.

Entity Validity Rating and Recognition

In some embodiments, an entity including, but not limited to, a speaker,author or another entity (e.g. corporation) has a validity rating thatis included with the distribution of information from him/it (forexample, see FIG. 3, screenshot 304). For example, if a politician hasbeen found to have misstated the truth, an indication of such is able tobe displayed when he appears on a television program. In anotherexample, when a commentator appears, statistics of how many factuallyaccurate statements have been made by him and/or factually inaccuratestatements have been made by him are presented during the show. In someembodiments, parameters related to the statistics are able to beselected (e.g. specific to a show or a time period). In someembodiments, a running tally is presented throughout the show. Theindication is able to include any information including, but not limitedto, statistics, highlighting, the other indications described hereinand/or any indication to further inform the audience of histrustworthiness. In the example further, text appears on the televisionscreen, such as at the bottom, which states, Senator A has misstated thetruth 10 times, but has been truthful 20 times. The severity of themisstatement is also able to be factored in when rating a person orentity. For example, stating that something occurs 90% of the time butin reality it occurs 89% of the time is a minor and possible ignorablemistake. However, stating something occurs 90% of the time when itoccurs 20% of the time is not likely a rounding error or a slip of thetongue. Additionally, the subject of the mistake is also able to betaken into account in terms of severity. For example, if a person makesan untrue statement about the country of origin of baseball, that is aminor mistake, whereas making an untrue statement about tax informationis a major mistake, and the major mistake is weighted more than theminor mistake. In some embodiments, an independent agency determineswhat is major and what is minor. In some embodiments, individual usersare able to indicate what is important to them and what is not. In someembodiments, another implementation of determining what is major, minorand in between is implemented. The context of the situation/statement isalso able to be taken into account. In some embodiments, entities areable to fix their validity rating if they apologize for or correct amistake, although measures are able to be taken to prevent abuses ofapologies. Another specific form of indication includes gradients ofcoloring such that a truthful person is highlighted with a border inbright green, and the green becomes less bright as the truthfulness ofthe person decreases and becomes red when they are viewed as less thantruthful, ultimately reaching bright red when considered completelyuntruthful. Any combination of colors is able to be used, or any otherindication described herein is able to be used. In some embodiments, inaddition to or instead of a validity rating, an entity is able toinclude another rating, including, but not limited to, a comedic ratingor a political rating. In some embodiments, an entity includes aclassification including, but not limited to, political, comedy oropinion. Examples of information or statistics presented when an entityappears include, but are not limited to the number of lies,misstatements, truthful statements, hypocritical statements or actions,questionable statements, spin, or any other characterizations. In someembodiments, the information or statistics are available through a link,mouse-over, picture-in-picture or other implementation. In someembodiments, specifics of the statements are able to be viewed; forexample, by clicking on “hypocritical statements,” a list of thehypocritical statements is presented to the user. In some embodiments,both the hypocritical statement and the source statement are shown. Insome embodiments, the source for one or both of the statements is shown.Additional statistical information is available too, including, but notlimited to, the severity of the statement (e.g. egregious lie versusminor mistake). In some embodiments, users are able to specify an amountof statements shown: by number of statements, by time period ofstatements (e.g. last 6 months) or by any other implementation. Forexample, Person X's last 5 hypocritical statements (out of 30) areshown. In some embodiments, dates or time frames are used in determiningthe relevance of fact check comparison. For example, if a hypocriticalstatement was made 30 years ago, the fact checker may realize that itwas more likely a change of view rather than a hypocritical statement;whereas, a contradictory statement made 2 weeks ago is likely due tohypocrisy not a change of view. In some embodiments, friends, familymembers, co-workers, users and others have validity ratings.

In some embodiments, the entity rating is implemented using a databaseor other data structure. For example, the database includes a column orrow with names and their corresponding entity rating. In embodimentswhere additional information is stored, additional column(s) includespecific information such as hypocritical statements, severity of themistakes, and any other information. The database is then used to lookup the entity's information for indicating the information.

In some embodiments, people/face recognition is implemented. Forexample, a politician is on a talk show, and the face recognitionidentifies the politician. Once recognized, information about thepolitician is displayed including, but not limited to, the validityrating described herein, statistics, and/or other information. In someembodiments, the information posted includes quotes of most outrageousthings said, most truthful things said, or other specific quotes.Similarly, other recognition is able to be implemented including, butnot limited to, voice recognition or biometric recognition. For example,a mobile application recognizes who is talking by voice recognition andposts a validity rating and/or other information on the phone. In otherexamples, at a dinner party the mobile application is able to identify aperson who tells tall tales, or at a negotiation, the application isable to indicate if the opposing side is honest. Voice recognition isalso able to identify someone on a television show or radio show. Insome embodiments, users' online/screen/usernames are identified. In someembodiments, a person's identity is input by a user, and theninformation is displayed about that person. FIG. 6 illustrates exemplaryimplementations including facial/people recognition 602.

In some embodiments, when an entity is displayed (e.g. on a devicescreen), the entity's positions on topics are displayed. For example,political positions are displayed (e.g. pro-life, pro-choice, anti-tax,others). The positions are able to be regarding a lighter material thanpolitical positions such as personal preferences regarding foods,entertainment and any other information. In some embodiments, differentmagnitudes regarding the positions are able to be displayed. Forexample, if someone is a fervent anti-war activist, the person's fervoris indicated. In some embodiments, evidence is provided showing theentity's position. For example, a voting record is shown to indicatethat the person may be saying she is against raising taxes, but voted 10times to raise taxes while in Congress. FIG. 6 illustrates exemplaryimplementations including entity information 604.

Flagging

In some embodiments, users are able to flag statements. FIG. 6illustrates exemplary implementations including flagging information606, where highlighting text is shown. Users are able to flag thestatements using Twitter, polling, text messaging (e.g. SMS or MMS),audio texts, video texts, phone, voice, selecting (e.g. with a mouse,keyboard, remote control, hand-waving, body-motion capture, touchless 3Dinput or joystick), highlighting, copying, or any other implementationof flagging a statement. In some embodiments, a flagged statement isthen highlighted or another effect is applied. Flagging is also able toinclude a “thumbs up”/“thumbs down” or “happy face”/“frown”representation, for example, users who feel the statement is valid wouldgive a “thumbs up.” Although the word “flag” is used, the strictdefinition is not implied. Any form of highlighting, pointing out,commenting on, selecting, or linking to is able to be implemented.Comments are able to be flagged as valid/true, invalid/untrue,questionable, unverifiable, depending (on context) or using a scaleincluding, but not limited to, 1-10, where 1 is blatantly false and 10is definitely true. Comments are also able to be flagged as spin,comedy, sarcasm, hyperbole, hypocritical and/or any othercharacterization. Comments are able to be flagged to force them to befact checked (e.g. manually forced fact checking). Additionally,comments are able to include support for the flag, including, but notlimited to, a citation supporting or proving the user's position. Insome embodiments, the users who flag statements are rated. For example,the users are rated by comparing their flagging with results of a factcheck. In some embodiments, if a user is wrong often, then his flag isnot used. In some embodiments, if a user's rating is or falls below athreshold, the user is ignored. In some embodiments, separate classes ofusers are implemented for flagging, including, but not limited to,media, viewer, and professional. In some embodiments, if a user iscorrect often, his flag is used and is able to have a stronger value. Insome embodiments, a weighting scheme is used such that a value of auser's flag is proportional to the correctness of previous flags. Forexample, if User A flags 100 items as wrong, and after a fact check, theuser is found to have wrongly flagged 95 items, that user's future flagswill have little weight or will possibly be ignored; whereas, if User Bflags 100 items as wrong, and after a fact check, the user is found tohave correctly flagged 95 items, that user's future flags will haveweight and possibly additional weight compared to others. In someembodiments, a competition is implemented using flagging where users areasked to assess the validity of statements, and the user who is correctthe most often wins the competition. Any other competitions involvedwith fact checking are possible as well.

Structure, Execution and Sources

In some embodiments, a site is specifically designed (e.g. formatted)for data verification or fact analysis. For example, common quotesand/or data are appropriately formatted to be compared with other text,speech or any other communication. In an example, speech checking occurssuch that if a commentator says, “Person A said X, Y and Z,” a digitalversion of the transcript would be located and compared to determine ifPerson A actually said X, Y and Z.

In some embodiments, the fact checking system has the ability to learn.The learning is able to be in terms of context, detecting items likesarcasm, cheating or manipulation of data sources and other items thatwould help the fact checking process. In some embodiments, a database isused to track people's comment habits or history and other information.For example, if Person X is known for using hyperbole, the fact checkingsystem is able to recognize that and then provide future indicationsusing such knowledge. In some embodiments, new sources are able to befound using learning. For example, a crawler, data miner, bot, and/orother implementation is able to search for and utilize additionalsources of information for fact checking. Learning is also able toinclude analyzing archived data of sources to determine the reliabilityof the sources. In some embodiments, if a characterization or other itemhas not been learned, an expandable list of options is presented to auser for the user to select an option.

In some embodiments, an auto-correction feature is implemented. Forexample, if text is being monitored, when a factual statement isinaccurate, the text is automatically changed. In some embodiments, theuser is asked if they want to correct the statement. In someembodiments, the flawed text is merely indicated including, but notlimited to, underlined, highlighted or change in font/color. In someembodiments, in video, the auto-correction feature automatically poststext on the video with the correction.

In some embodiments, specific phrases known to be true or false areadded to a database and/or a website, so that the fact checking systemis able to indicate the correctness of the phrase. For example, if onenews organization is known for misquoting someone and continuing to usethe misquote instead of the correct quote, that is able to bedetermined, and the quote is indicated as incorrect. In someembodiments, the correct quote is displayed or is accessible (e.g.through a hyperlink).

In some embodiments, determining which phrases to be fact checked isperformed automatically (e.g. by a computing device). In someembodiments, determining which phrases to be fact checked is performedmanually. For example, while a television broadcast is occurring, one ormore individuals select segments of the broadcast to be fact checked. Asa further example, if a person says, “we need to do something abouttaxes, unemployment is at 10%,” the first part of that sentence probablydoes not need to be fact checked or is labeled an opinion, but“unemployment is at 10%” is an easily verifiable fact. In someembodiments, manual and automatic fact checking are implementedtogether. For example, a user selects a sentence to be fact checked outof a paragraph, but a device automatically parses the sentence forseparate phrases to be fact checked.

In some embodiments, information is checked for being stale or outdated.For example, if a news organization runs a story that occurred manymonths ago but presents the story as occurring recently, the factchecking system is able to alert the user by presenting a date of whenthe story initially occurred. Determining if the information is stale isable to be performed in any manner including, but not limited to, a datecomparison. In some embodiments, fact checking is updated as informationchanges. For example, saying X is running for President may be labeledas “uncertain” at one point, but then when X officially declares that heis running, the label is changed to “true.”

In some embodiments, the source of the information to be checked and/orthe organization presenting the information to be checked are related toand/or are working in cooperation with the fact checking system. Forexample, a news organization implements its own fact checking system topresent results to viewers. In some embodiments, the source of theinformation to be checked and/or the organization presenting theinformation to be checked are unrelated to and/or are not working incooperation with the fact checking system. For example, a companyindependent from the news organization implements the fact checkingsystem on a user's mobile device so that when the mobile device receivesinformation from the news organization, the mobile device performs thefact checking.

In some embodiments, caching is implemented to speed up the factchecking process. Caching is able to be implemented in any manner. In anexample, if Commentator X is known to spread the same lie, that specificlie is not re-checked; rather, when that lie is made, an indication thatthe statement is a lie is presented based on cached analysis of thestatement. In some embodiments, cached data is re-checked periodicallyto ensure the data does not become stale. In some embodiments, there-checking occurs in the background to avoid interruption of any otherprocessing.

Any search algorithm, sorting algorithm, data structure and/or otherdata organizational or analysis scheme is able to be used to implementthe fact checking system and any other systems described herein. Forexample, advanced search algorithms, advanced search text algorithms,indexing and searching by indices, including combinations of searchimplementations, are able to be used. Data structures including, but notlimited to, arrays, queues, maps, buffers, tables, matrices, lists,trees, heaps, graphs, classes and subclasses, databases, and otherstructures, including combinations of data structures are able to beused. The search, sorting, data structure and/or other dataorganizational or analysis scheme is able to be used in any aspect ofthe fact checking system including, but not limited to, locatingsources, organizing sources, comparing information with sourceinformation, searching within sources, storing sources and any otheraspect. In another example, a data structure is used for implementingthe fact checker and/or providing supplemental information by storingrelationships and/or related items, including, but not limited to,arguments/opposing arguments, misquotes/correct quotes,brands/competitors, and/or any other items.

In some embodiments, pattern recognition of recognizing a pattern isimplemented in any aspect of the fact checking system. For example, thepattern recognition is implemented in monitoring information. In anotherexample, the pattern recognition is implemented in processing theinformation. In another example, pattern recognition is implemented infact checking including, but not limited to, locating sources,organizing sources, comparing information with source information,searching within sources, storing sources and any other aspect.

In some embodiments, a queue or other structure is implemented to storefacts or other items to be checked when a connection is not available.

In some embodiments, sources are rated based on popularity or“trending.” For example, if Site X has 1,000,000 individual hits perday, and Site Z has 50 individual hits per day, Site X has a higherpopularity. Popularity is able to be established using any methodincluding, but not limited to, total hits per time frame, unique hitsper time frame, quantity of links to the source, quality of linkingitems to the source, duration of existence of the source, any othermethod and/or any combination thereof. Any of the sorting, filtering andapplying of thresholds described regarding reliability ratings andsources is able to be applied to popularity and sources. For example,the fact checker is able to be limited to sources with a popularityabove a specified threshold. In some embodiments, both popularity andreliability are implemented in determining which sources to use. In someembodiments, other reliability determinations are used with thepopularity rating to determine the reliability of a source.

In some embodiments, the sources are ordered by reliability (forexample, as shown in FIG. 7), and when information is fact checked, theprocess of fact checking starts the search with the most reliable sourceand continues to less reliable sources. In some embodiments, a structuresuch as a tree, list or any other structure includes pointers to thesources ordered by reliability. In some embodiments, the order isdescending order from most reliable to least reliable. In someembodiments, the order is ascending order from least reliable to mostreliable. In some embodiments, the order is configurable. In someembodiments, a fact checking search stops after N (e.g. N=2) sourcesverify the fact.

A short version of an exemplary list of sources ordered by reliabilityincludes:

1. a link to the Random House Dictionary website with a reliabilityrating of 100% reliability,

2. a link to the Britannica Online Encyclopedia website with areliability rating of 100% reliability,

3. a link to the XYZ News website, with a 90% reliability, and

4. a link to Bob's made-up-opinion-on-all-things website, with a 1%reliability.

In some embodiments, multilevel fact checking is implemented. Forexample, a phrase is fact checked, but before the fact check iscompleted, the source is fact checked to determine if the source isreliable. The multilevel fact checking is able to continue until areliable source is found, and then the fact check of the phrase iscompleted with the reliable source.

In some embodiments, sources are classified as fact/objective andopinion/subjective. For example, a data structure such as a tree isimplemented with objective sources on one side of the tree andsubjective sources on the other side of the tree. In another example, asone goes left to right at the bottom of the tree, the sources go frommost objective to most subjective. The sources are able to be classifiedby determining what the majority of their content is, by beingclassified by a user, by including a classification tag, or any othermethod.

In some embodiments, a determination of whether information is taken outof context is made. The determination is made by comparing the audio,video, text and/or other content used with the original or full version.For example, if a news organization shows a clip (e.g. portion of avideo), the entire video is made available to a user for a period oftime before and/or after of the clip is shown. For example, 30 secondsof the video before the clip started is shown.

In some embodiments, the data verification or fact checking occurs on aremote server including, but not limited to, a central server. Theresults are able to be cached and/or sent to users' local machines. Insome embodiments, the data verification or fact checking occurs at auser's local machine. In some embodiments, the data verification or factchecking occurs using cloud computing.

The fact checking system is able to be implemented on a separate devicethat couples or communicates with a television; as part of a television,radio or Internet broadcast or any other broadcast; on a mobile deviceincluding, but not limited to, an iPhone® or Droid®; on a computer; on atablet including, but not limited to, an iPad®; or any other device.

In some embodiments, the fact checking system is a smartphoneapplication including, but not limited to, an iPhone®, Droid® orBlackberry® application. In some embodiments, a broadcaster performs thefact checking. In some embodiments, a user's television performs thefact checking. In some embodiments, a user's mobile device performs thefact checking and causes (e.g. sends) the results to be displayed on theuser's television and/or another device. In some embodiments, thetelevision sends the fact checking result to a smart phone.

In some embodiments, parallel monitoring, processing, fact checkingand/or indicating is implemented. For example, two or moreimplementations of a fact checker are used. In the example, the two ormore implementations are able to be on the same device or on differentdevices. In a further example, each implementation is different, andthen the results of each are compared to determine a “best” resultand/or to provide several results. For example, one implementation of afact checker excludes certain sources, while another fact checker usesall sources, and their results are able to be different, and in someembodiments, the different results are presented to a user and/orratings are provided with the results and/or other information isprovided. In some embodiments, monitoring and processing are implementedin parallel with fact checking. For example, one device monitors andprocesses information and a second device performs the fact checkingwhile the monitoring and processing occurs. In some embodiments,pipelining is implemented. In some embodiments, distributed processingis implemented. For example, multiple devices perform fact checking(e.g. searching, comparing and returning results) and return a compositeresult. In some embodiments, separate fact checkers are implemented tofact check multiple data providers (e.g. broadcasters, newspapers,websites and/or any other communications/information). In someembodiments, the fact checking multiple data providers occurs at thesame time, and in some embodiments, the fact checking occurs atdifferent times. For example, 3 fact checkers are implemented to factcheck 3 major cable news networks. In some embodiments, one fact checkeris able to fact check multiple data providers at the same time. Whenfact checking multiple data providers, the information from each is ableto be shared, compared, and/or any other processing/analysis is able tobe performed. For example, if 5 out of 6 data providers lead with StoryA, but the 6th data provider leads with Story B, an indication is ableto be made that Story B is presenting different information. In someembodiments, multiple fact checkers are used to fact check differentaspects of a show. For example, a first fact checker is used to factcheck historical information, a second fact checker is used to factcheck charts and graphics, and a third fact checker is used to providesupplemental information.

Supplemental Information

FIG. 8 illustrates an example of providing supplemental informationbased on information from a television 800 where the supplementalinformation is displayed on a user's mobile device 802. In someembodiments, the fact checking system provides clarifying comments oradditional (or supplemental) information to assist a user or viewer. Forexample, if a commentator makes a general statement that the cost of acleanup will cost X dollars, the fact checking system is able to findspecifics regarding the cost and provide a detailed explanation of eachcomponent of the total cost.

FIG. 9 illustrates a flowchart of a method of providing additional orsupplemental information according to some embodiments. In the step 900,information is monitored. For example, broadcast information (e.g. atelevision program or advertisement) is monitored. In the step 902, theinformation is processed. For example, the information is parsed. In thestep 904, additional or supplemental information is searched for andreturned. For example, a database is searched to find opposing argumentsto an argument, or supporting arguments are searched for on web pages,or a competitor's advertisement is located in a database, or any othersupplemental information is found and returned. The amount ofinformation returned depends on the implementation. For example, a linkto a webpage could be returned, a link to a video, the video itself,text, and/or any other information is returned. In the step 906, thesupplemental information is indicated or displayed. For example, anopposing argument is displayed on a mobile device. As described herein,monitoring, processing, searching and indicating are able to beimplemented in many different ways and are able to include manydifferent items.

In some embodiments, supplemental information is provided withoutperforming the step of fact checking. For example, monitoring,processing and indicating still occur, but instead of fact checking,supplemental information is found and returned. As an example, a newsshow is monitored, processed (e.g. converted and parsed), and thensupplemental information is determined (e.g. located) and indicated. Forexample, a person discusses a new candidate from North Dakota, NorthDakota is searched for and is found in an encyclopedic source, some orall of the encyclopedic information is retrieved, and supplementalinformation providing statistics about North Dakota is shown. In anotherexample, a person states, “the U.S. debt has been growing significantlyunder this President;” supplemental information is able to be displayedshowing U.S. debt growth under some or all of the previous Presidents.In another example, if a complex issue is discussed, clarification isprovided. For instance, if a complex economic issue is discussed, theissue is broken down into simpler parts. In yet another example, ifsomething is explained incorrectly or not clearly, clarification isprovided. For example, during the Presidential race, national polls aredisplayed regularly; however, national polls mean very little due to theElectoral College election system of the U.S. Therefore, supplementalinformation providing battleground state polling is able to be shown tosupplement the national polls. In some embodiments, supplementalinformation is provided for both sides of an argument. Any of the othersteps and implementations described herein are applicable to providesupplemental information without fact checking.

In some embodiments, supplemental information includes an advertisement.In some embodiments, a price comparison is displayed. In anotherexample, a viewer is watching an awards show and on the red carpet,celebrities are wearing designer brands of attire, and an advertisementfor each dress/suit/shoe/clothing/jewelry/items is displayed (or asimilar knock-off item is displayed). In some embodiments, thesupplemental information is presented on the same device the user iswatching (e.g., television). In some embodiments, the supplementalinformation is presented on a separate device such as mobile deviceand/or another device. In some embodiments, the supplemental informationis a Tweet, an email, a text message and/or any other communication. Insome embodiments, the advertisement is presented during the programbeing viewed, and in some embodiments, the advertisement is presentedafter the program is viewed.

In some embodiments, supplemental information is provided based on aheadline, title, caption, talking point and/or other short phrase. Forexample, titles (or any other short phrases) are monitored, processed,fact checked and a result is indicated. In some embodiments, the step offact checking is replaced with finding supplemental information. Byfocusing on just the title, less processing takes place. For example, ifa news program begins the show with “Nasdaq Hammered,” statisticalinformation of the worst days for the Nasdaq are indicated for the user.In another example, if a headline states, “Taxes Going Up,” supplementalinformation that specifies which taxes are going up, by how much andwhen the taxes are going up is indicated. Or in some instances, rebuttalsupplemental information that indicates taxes are not going up (e.g. ifthe information is outdated or new information showing taxes are notgoing up) is presented. The amount of supplemental information is ableto be as short as a single word (e.g. False!) or as detailed as a 200+page study or anywhere in between and including any kind of informationto provide the user with more information. In some embodiments, analysisof only the title (or other heading) is used for an opposing view to bepresented. For example, if a headline states, “Global Warming CausingWildfires,” supplemental information of an opposing view that discusseshow the wildfires are caused by La Niña is presented.

Supplemental information is found and returned in any manner, including,but not limited to, the same or similar manner(s) described regardingfact checking. For example, information is searched for by comparing theinformation with sources, and information related to the searched forinformation is returned. In another example, the supplementalinformation is stored in a data structure such as a database or table.

In some embodiments, one or more opposing arguments are indicated inresponse to content or information. In some embodiments, the opposingarguments are based on fact checking information. In some embodiments,the opposing arguments are indicated without fact checking theinformation; rather, opposing arguments are determined and presented.For example, an argument is determined, the argument is classified, anopposing argument is determined, and then the argument is presented. Insome embodiments, a table (or other data structure) contains argumentsand matching opposing arguments. In some embodiments, the opposingargument or supplemental information is based on politicalclassification. In some embodiments, a set of links of arguments arecoupled with opposing arguments. For example, a pro-life argument isdetected, which finds that argument in the table, and then thecounter-argument coupled with the argument is found. FIG. 10 illustratesan exemplary table of arguments and counter-arguments according to someembodiments. Sub-arguments and sub-counter-arguments are also able to beincluded. In another example, if a person makes a comment with aposition, an opposing position is indicated without fact checking theposition. To further the example, if a guest on a political show makes acomment, an opposing position is indicated on the television screen intext. Indicating the opposing position is able to be in any manner asdescribed herein (e.g. text on a television screen or text on a mobiledevice). In some embodiments, determining the opposing argument is ableto be based on keywords detected, based on the speaker/author/entity ofthe position, based on political leanings of the speaker/author/entity,based on context, based on metadata, and/or based on any other detectiondescribed herein. For example, if a keyword of “abortion” is detected,and the speaker is a strict conservative, a description of a liberalview is presented. In another example, if keywords of “President” and“economy” are detected by a liberal commentator, context is able to beused such as the current date to determine which President is beingdiscussed, and economic data, past and present, including comparisons,is able to be presented to the user. Such additional information wouldhelp guarantee a balanced presentation of information to users.

In some embodiments, an opposing advertisement is presented when anadvertisement is presented. For example, if there is a commercial forBeer X displayed on the television, a commercial for Beer Y is displayedon the user's mobile device, on a smaller section of the television(e.g. bottom of the screen), or another device. FIG. 11 illustrates anexemplary table with Brand X and Brand Y, where when a Brand Xcommercial is detected, a Brand Y commercial is displayed on the user'sdevice, or vice versa. In some embodiments, a fee scheme is implementedwith this to collect advertising money from Brand Y. In someembodiments, multiple companies/products are included within the table(e.g. Brand X, Brand Y and Brand Z), and when one is detected one ormore of the others is displayed (e.g. in a random manner, in analternating manner, based on advertising fees by the brands, or in anyother manner). In another example, when an advertisement for a newmedicine is detected, supplemental information providing the sideeffects and other negatives is displayed. In another example, anopposing political advertisement is displayed. In some embodiments, thegroupings of the arguments or commercials/products/companies aregenerated automatically (e.g. based on searches), and in someembodiments a user inputs groupings, or both are implemented. In anotherexample, an advertisement for Candidate X is displayed, and anadvertisement for Candidate Y is displayed on the same device or anotherdevice. In some embodiments, a correction or contradiction to anadvertisement is displayed. For example, an advertisement says,Candidate X raised taxes N times, and a correction and/or advertisementexplains Candidate X never raised taxes. As described herein, anautomatic rebuttal is able to be implemented. For example, if CandidateX knows of the advertisements run by Candidate Y which attack CandidateX, Candidate X is able to generate advertisements that directly refutethe attacks which are then run at the same time or in response to theCandidate Y advertisements (for example, using a table similar to FIG.11 where Candidate X and Candidate Y are in the same row of the table oranother form of linking). In some embodiments, the original content(e.g. advertisement) and the opposing content are displayed on the samedevice, and in some embodiments, the original content and the opposingcontent are displayed on different devices (e.g. original on television,opposing on mobile device or vice versa). As described herein, in someembodiments, a commercial or advertisement is detected based on aproduct, a company and/or language in the commercial/advertisement,metadata, or any other method. For example, an advertisement for SodaBrand X by XYZ Corp. is detected based on monitoring for “Soda Brand X,”“XYZ Corp.” and/or a catch-phrase or other language used incommercial/advertisement. In some embodiments, acommercial/advertisement is detected using another implementation.

In some embodiments, opposing arguments are presented by an opposingentity including, but not limited to, a website, televisioncompany/network/station, person, company and/or other entity.Information is able to be monitored, processed, compared with/searchedfor (e.g. in a lookup table or database) and then the opposing argumentis presented. For example, a first entity is able to fact check and/orrespond to another entity with the first entity's analysis (possiblybiased analysis). The first entity makes selections of how to factcheck, analyze and/or respond. The selections include but are notlimited to the site/station/network/show to analyze, keywords orarguments to look out for, responses to arguments, sources to use,styles of responses, format of output, and/or any other selections. Forexample, a conservative blogger selects a liberal news organization tomonitor, specifically indicates to automatically monitor for “globalwarming” and indicates a set of links to books and articles to bedisplayed that present an opposing view of global warming. Then, when aviewer is watching programs from that organization, any time globalwarming is discussed, the viewer is presented the set of links. In someembodiments, the arguments and opposing arguments are stored in a datastructure such as a table. In some embodiments, the selections aregrouped by political classification (e.g. liberal, conservative or anyothers) and/or grouped by other classifications, for example, so theuser only has to select his political classification without specifyingother details. In some embodiments, a user makes selections (e.g.specifying that he is a conservative), and in some embodiments, theselection is automatic. The automatic selection is able to be based onanalysis of websites the user visits (e.g. browser history shows he goesto liberal websites, so automatically select liberal), based onpurchases the user makes (e.g. buys “green” products, so automaticallyselect liberal), based on television/radio shows watched/listened to(watches conservative talk show, so automatically select conservative),and/or any other automatic selection. In some embodiments, a database orother data structure is used to classify and store the websitenames/links, television shows, and any other information. In someembodiments, a user's selection is automatically generated based onsocial networking information such as associations (e.g. if Facebook®friends are conservative, assume user is conservative). In someembodiments, users are able to make several selections to furtherspecify their orientations (e.g. selecting: socially liberal, fiscallyconservative, and environmental). The selections are able to be verybroad, very specific, somewhere in between, and are able to be manyselections or a single selection.

In some embodiments, advertising is presented based on a user'sselection(s) and/or classification(s). In some embodiments, advertisingis presented based on the monitored language. For example, if a user isindicated as liberal and a global warming topic is monitored, a Priusadvertisement is presented. Additional information regarding the user isalso able to be incorporated in determining the advertisement to bepresented. For example, if the user is a new mom and liberal, and anenvironmental topic is presented, an advertisement for “green” diapersis presented. FIG. 12 illustrates an exemplary data structure (e.g. adatabase or a table) implementing selections and advertising. In theexample, user selections/information, keywords to monitor andadvertisements are maintained, as well as any other relevantinformation. Further in the example, user information includes that theuser is a liberal and an environmentalist, therefore the keyword/phrase“Global Warming” is monitored for, and when detected, an advertisementfor a Hybrid X Vehicle is displayed. In some embodiments, recent searchhistory of the user is also included in the data structure.

In some embodiments, supplemental information is indicated forentertainment shows. For example, if a television show is about teenpregnancies, then educational videos, images, links, statistics, games,advertisements, or any other information is indicated. The supplementalinformation is able to be found using any implementation such as by thesearching and comparison described herein including searching a datastructure (e.g. a database) which stores the information to be presentedin response to the entertainment information. In another example, if theshow appears to glorify teen pregnancies, information regarding thenegatives of teen pregnancy is presented. Similarly, if a televisionnetwork is promoting purchasing housing or even “flipping” housing,negatives of owning housing or the dangers of “flipping” housing arepresented. In some embodiments, specific details about the “flipped”house are shown, for example, the purchase price, the expenses, and thesales price. For sports shows, statistics and/or other information isshown. For example, if a user is watching a football game on televisionor on his mobile device, and the game is in the fourth quarter, and thequarterback just threw a completion, additional information is presentedon the user's television or mobile device which shows statistics (e.g.game statistics, historical statistics, other statistics, personalinformation, other information) of the quarterback. For example, toincrease the viewing audience, the personal information could beinformation that would interest a person not interested in footballitself, including, but not limited to, the player's girlfriend, age,alma mater, home town, likes/dislikes, and other information to enticeother viewers to watch. In some embodiments, the supplementalinformation explains the sport/game including, but not limited to, whatjust happened, why there was a penalty, the rules of the sport/game(e.g. how to play Texas Hold'em), the purpose of the sport/game and/orany other explanation to help the audience. In some embodiments, thesupplemental information provides an easy way to purchase items. Forexample, a football jersey advertisement is presented for the jersey ofthe player who just had an exciting play. The way to purchase theitem(s) could be a link to a store to purchase the items, a singlebutton purchase or any other way of providing sales. The supplementalsales information could be related to a commercial or advertisement. Forexample, if a commercial is displayed for X Brand mountain bikes, then astore locator is displayed on a user's device indicating where topurchase the X Brand mountain bike, or an online site with a link topurchase the item (e.g. bike) is presented. In some embodiments, when amovie is being played, related movies are presented or informationincluding, but not limited to, a description, rental information, andpurchase information is presented. In some embodiments, if a movie orother item is referenced in another movie, television show, or othercontent, a clip, transcript or other information of the movie or otherreferred item such as a book or a poem is presented. For example, whenGeorge sings “Master of the House” from Les Miserables in “Seinfeld,” aclip of the musical is shown or lyrics are displayed on the user'sdevice.

In some embodiments, the supplemental information is related to sportsbetting/play-along including, but not limited to, fantasy football andcollege basketball brackets, where a user's fantasy team or bracket isupdated automatically in sync with the game results. For example, if abasketball game ends, the user's bracket is automatically updated andpresented on the user's device including the current standings. Inanother example, as the football games occur, a player's fantasy teaminformation is updated during the games and presented on the user'sdevice.

In some embodiments, news, weather, traffic and/or other information isfact checked by comparing the information with other stations' results(e.g. fact checking by comparison with peers is performed). For example,if News Company A states Candidate X paid $0 in taxes last year, butNews Company B, News Company C and News Company D all say, Candidate Xpaid $100,000 in taxes, the additional information is presented to theuser. In another example, if meteorologist at Channel A says it will be80 degrees today, but meteorologists at Channels B through D and onlinesites Y and Z say it will be 90 degrees today, the additionalinformation is presented to the user. In some embodiments, if a story(e.g. news story) is incomplete on one station, or another station hassupplemental information, that information is presented to the user. Forexample, if one station does not indicate the victim's race, but anotherstation does provide this information, that supplemental information ispresented (e.g. as text at the bottom of the screen with credit given tothe providing source). Determination of the missing information is ableto be by comparing keywords in the information, processing andformatting the information (e.g. by searching for specific items in astory and determining if any information is missing) or any otherimplementation. For example, for a news story about a homicide, a datastructure contains elements for race of the attacker and victim, age ofthe attacker and victim, motive, location, weapon, and any otherinformation. And if any of the information is unknown from onechannel/site/network, other sources of information are able to be usedto fill in the missing information.

In some embodiments, supplemental information is provided by the samesource that is providing the original content (e.g. XYZ Networkbroadcasts a political show and also provides supplemental information).In some embodiments, supplemental information is provided by a thirdparty (or independent party). For example, XYZ Network broadcasts apolitical show, and TTT App provides supplemental information to bedisplayed with the political show, where TTT App has no affiliation withXYZ Network.

In some embodiments, supplemental information is provided when the factchecker is used for print articles. For example, after a user acquirescontent of an article in a magazine, supplemental information related tothe article is provided including, but not limited to, where to buy anitem in the article, what the latest study says about the content of thearticle, and any other information.

In some embodiments, a running log of supplemental information is kept.In some embodiments, the running log is user-specific and/ordevice-specific. For example, the supplemental information for Bob isbased on what Bob has been viewing, reading and/or receiving. In someembodiments, by keeping a log of the supplemental information, repeatedindication of supplemental information is avoided. For example, if aviewer of a television show has already been provided with supplementalinformation about a character, that supplemental information is notautomatically shown again. In an additional example, a data structurestores information indicating what supplemental information has beendisplayed to a specific user, and then that information is used todetermine what supplemental information to display, if any. In someembodiments, updated supplemental information is shown based on theprevious supplemental information. For example, if character informationhas previously been shown to a user, but there is new information sincethe user missed a week, only the new information is shown. In someembodiments, a history of supplemental information is kept, so that theuser is able to search and/or look through this information on demand.

In some embodiments, when numbers or charts are described in words (e.g.in a broadcast), supplemental graphics are displayed. In someembodiments, when a trend or statistics are mentioned, graphics aredisplayed to show the trend. For example, a reporter says, “housingprices have decreased for 5 months,” and then supplemental informationis shown that includes a chart of the past 5 months of housing prices byretrieving 5 months of data and generating a chart using a chartgeneration application. Providing the supplemental information isperformed in any manner; for example, by finding the data and generatinga chart and/or finding the chart. In some embodiments, context is used;for example, if the comment is “over the past 6 months,” then today'sdate is used to find data going back 6 months.

In some embodiments, supplemental information is generated in advance ofa broadcast based on a guest list for the show or other knowledge of theshow. For example, the guest information such as views, biases,political party and/or any other information is able to be located andprepared beforehand for a political guest. Or for an actor appearing ona late night show, recent movies, events in the personal life of anactor, or other information is prepared in advance. In some embodiments,the advanced generation of information is performed automatically, andin some embodiments, the advanced generation of information is performedmanually.

In some embodiments, supplemental information is based on personalconditions, personal traits, recent events and/or other information. Insome embodiments, the information is able to be taken from a socialnetworking site (e.g. Facebook®) or a site/implementation such asTwitter. For example, if a user indicates his mood on a socialnetworking site, that information is able to be used in providingsupplemental information. In some embodiments, the supplementalinformation is used in generating a suggested list of channels and/orprograms for the user. For example, if the user indicated “depressed,” alist of comedies is presented to the user. In another example, if theuser indicated “depressed” and “conservative,” comedies with aconservative slant are presented (or at least presented first in adescending order starting with the most conservative). The supplementalinformation is able to be used in presenting advertisements to the userin combination with or without other elements described herein. In someembodiments, the information (e.g. mood) is fact checked.

In some embodiments, when a word or phrase is mentioned (e.g. in amovie, on the news, in a television show, in person, in a discussion, onthe Web and/or elsewhere), supplemental information is providedregarding that word or phrase. In some embodiments, only words orphrases that are included in a data structure (e.g. database) to providesupplemental information are used. In some embodiments, common phrases(e.g. don't look a gift horse in the mouth) are used. In someembodiments, only words and phrases deemed to be “not well known” areused. For example, if a movie makes a reference to an obscure object orperson, supplemental information is provided so that the userunderstands what or who that object or person is. As described herein,the word or phrase is able to be searched for in a data structure, theweb and/or any other source, and the result of the source is returned(e.g. a definition of the word).

In some embodiments, a data structure, for example a database, a tableor any other data structure, is used to search for and presentsupplemental information. In some embodiments, supplemental informationis based on subsequent searches.

Importance/Relevance

In some embodiments, broadcast information, stories, articles, or othercontent is rated and/or classified in relation to a user. FIG. 13illustrates an exemplary listing of headlines with an importance ratingaccording to some embodiments. In some embodiments, the content is ratedbased on an importance or relevance to the user's life or based on theuser's interests. In some embodiments, the importance is selected by theuser, and in some embodiments, the importance is based on standards of agroup of people (e.g. neighborhood, town, state, country) such ascommunity standards. For example, a community may establish the economyas the most important topic, followed by national security, then taxes,and other items following. In some embodiments, a combination ofcommunity standards and user selections is used to determine importance.Thus, content focused on lower priority (less important) items is ratedlower than higher priority (more important) items. In some embodiments,content is presented to users based on the ratings (e.g. higher ratedarticles are presented at the top of a list to a user). In someembodiments, content that falls below a threshold is not presented to auser. In some embodiments, the user sets the threshold and/or specifieswhich kind of content not to show. For example, articles aboutPresidential wardrobes are not displayed to users where the user'simportance ratings have such content below the user's threshold. In someembodiments, users are able to search based on the importance rating. Inan example of a user-specified rating, a user selects lifestyle choicesas the most important topic followed by the environment. In someembodiments, user-specified ratings are based on social networking siteinformation, search information, preferences, favorites, city or stateof residence, and/or other selections. For example, if a user searchesfor economic data often, then the economy is designated as an importanttopic for the user. In some embodiments, content is rated using multipletopics. For example, an article is rated as to how religious it is, howeconomic-related it is and how environmentally-conscious it is. In someembodiments, the rating in relation to importance to a user is used incombination with other ratings to provide a more complete rating. Forexample, an article is rated highly (e.g., 10) in importance because itinvolves unemployment and creating jobs, but it is rated poorly (e.g.,4) for its lack of accuracy, so the combined rating is a 7 on a scale of1 to 10. In some embodiments, the separate ratings are presentedseparately (e.g., article is a 10 for importance and a 4 for accuracy).Any rating indication is able to be used (e.g., 1-10, A-F, a rainbowgradient of colors, or any other indication). In some embodiments,classification of content is determined based on keywords found withinthe content and/or any other classification. For example, if an articleuses economic terms such as unemployment, stimulus, and taxes, thearticle is able to be classified as related to the economy. In someembodiments, content is able to be classified in one or moreclassifications. In some embodiments, the rating and/or classificationof content is performed by monitoring, processing, keyword searching,and indicating. Keyword searching includes searching within the contentfor keywords. In some embodiments, monitoring or processing includeskeyword searching and/or detection. In some embodiments, the ratingand/or classification is performed automatically. In some embodiments,the rating and/or classification includes fact checking, and in someembodiments, fact checking is not performed. In some embodiments, thereare classifications and one or more levels of sub-classifications. Forexample, a news broadcast that uses the terms: “unemployment,” “stocks,”and “taxes” is able to be included in the class “economy” and thesubclasses “stock market” and “employment.” The importance rating isindicated next to a title, displayed at the beginning of a televisionprogram, displayed in the information of a television program guide,displayed on a mobile device, and/or any other indication. In someembodiments, the classifications are based on general topics including,but not limited to, politics, sports, entertainment, finance and others.For example, if a user has no interest in sports, the user is able toplace that at the bottom of the importance list. Using the sportsexample, “sports” could be the overall classification with specificsports (e.g., hockey, baseball, basketball, football, golf) assub-classifications, and NCAA® football and NFL® football as a furtherlevel of sub-classification. In some embodiments, the position of thearticle (e.g., pro/anti) affects the importance to a user.

In some embodiments, a likelihood of importance is indicated to a userand/or used to determine the importance of an article, where thelikelihood is based on the percentage of the population the articleaffects. In some embodiments, the position of the article (e.g.pro/anti) affects the likelihood of importance. In some embodiments,importance is based on what is trending now (e.g., what people aresearching for, texting about, and/or other popularity based data).

In some embodiments, importance to a user automatically increases ordecreases depending on the number of content (e.g., articles andtelevision shows) presented to and/or selected by the user. For example,a user selects many “economics” articles; therefore, they are likelyimportant to a user, thus the importance rating increases with time. Inanother example, a user has seen 10 television clips about the royalwedding, and the importance rating decreases with time since the user islikely tiring of the story.

In an example of an importance rating being implemented, a websitedisplays titles of 20 articles. The user viewing the website hasselected taxes, environment and foreign affairs as most important to theuser. Three of the articles are rated as 100s (scale of 1 to 100) on theimportance scale since they are focused on taxes (e.g., tax-relatedkeywords are detected), 5 are rated as 99s since they are focused on theenvironment and 1 article is rated a 98 since it is focused on foreignaffairs. The remaining articles fall below the user's threshold, and aregrayed-out or not shown, so that the user is able to focus on articlesimportant to him.

FIG. 14 illustrates a flowchart of a method of determining an importanceof information according to some embodiments. In the step 1400,information (e.g., an article) is analyzed. For example, keywords aresearched for in an article. To further the example, keywords arecompared with a database that classifies the keywords. For example, adatabase specifies that “global warming” is in an environment class, and“gun control” is in a constitutional class or a 2nd amendment class. Inthe step 1402, the information is then classified based on the analysis.For example, an article which uses the words or phrases, “pollution” and“global warming,” is classified as “environmental.” In some embodiments,information is classified in multiple classes. For example, if anarticle discusses guns and the environment, the article is classified ina “guns” classification and an “environment” classification. In someembodiments, the information is classified in only one classification,based on the most relevant classification. For example, if an articlecontains 10 keywords related to war and only 2 keywords related to theenvironment, the article is classified in a “war” classification. Insome embodiments, the classification includes a strength rating. Forexample, the percentage of occurrences, number of occurrences and/oranother analysis is used to determine how strongly the article isclassified. Furthering the example, an article is 90% composed ofkeywords related to war, thus, the article is given a “strong” rating ofbeing related to war. In another example, a lengthy article onlymentions the environment once; the article is given a “weak” rating ofbeing related to the environment. The strength rating is able to be usedin additional calculations in determining importance and/or separatelydisplayed. In the step 1404, the classification of the information iscompared with an importance, where the importance is able to beuser-defined, based on standards or a combination. For example, a useris recognized and has defined his “important” items to be theenvironment, the economy and sports. Furthering the example, if anarticle (e.g., environmental article) matches the user's most importantitem, the article is rated a 10 (e.g., most important). In someembodiments, an importance rating includes a user rating plus thestrength of an article. For example, a user rates the environment as histop priority, and an article is focused on the environment, the articleis rated as most important, but a second article merely mentions theenvironment, the article is rated as moderately important. In the step1406, an importance rating is indicated based on the comparison in thestep 1404. For example, since the user indicated environment as the mostimportant topic to him, and an article is determined to be about theenvironment, the article is given an importance rating of 10, which isdisplayed near the headline as is shown in FIG. 13. In some embodiments,fewer or more steps are implemented. Furthermore, in some embodiments,the order of the steps is modified.

In some embodiments, a channel is automatically changed when atelevision program discusses a story that falls below the user'simportance threshold, for example, by determining the importance of thestory, comparing the importance rating with the threshold, and if theimportance rating is or falls below the threshold, the channel ischanged. In some embodiments, the channel is changed to a story that ismost important to the user. For example, a user has selected 3topics—economy, sports, weather, and the user is watching News ChannelA, when the sports segment ends, and goes to a story about fashion, sothe television automatically switches to Channel B which is discussingthe economy. To make the switch, content on all or specified channels ismonitored and given an importance rating. In some embodiments, a videois changed in a similar manner to changing a channel. For example, if awebsite displays videos, and the current video is below an importancethreshold, the next video is presented. Similarly, a radio station orother program is able to be automatically changed based on a user'simportance threshold.

Bias

In some embodiments, a monitor of news stories and/or articlesdetermines if a story and/or article is being ignored or overanalyzed.For example, if 3 of 4 news networks cover a story, and the fourth newsnetwork does not cover the story or barely reports on it, a notificationor alert is presented to inform the user that he is missing the story.This is able to be implemented by comparing the stories, for example,comparing keywords or other information in the stories. This will helpprovide users with a full scope of news knowledge. In some embodiments,the notification includes a link or a guide to change the channel, sothe user is able to see or hear the story. In a similar but contrastingmanner, in some embodiments, stories are monitored to determine if theyare over reported. For example, if the same story is played on allstations, every 10 minutes, a notification or alert is presented toinform the user that the story is being over reported. In someembodiments, users are able to rate stories under reported, overreported or other ratings. For example, users are able to text a rating.Other methods of rating a story are possible as well. News networks arethen able to modify the presentation of news based on users' ratings. Insome embodiments, users register to be able to interact with a show orwebsite. In some embodiments, users have to qualify (e.g., pass a test)to be able to rate and/or post comments. For example, in someembodiments, users must prove they are not “trolls” by accuratelypredicting the factual accuracy of several statements.

In some embodiments, identifying framing of data including, but notlimited to, spin, slant, bias or any other framing or manipulation ofdata is implemented. Identifying framing of data is able to be done inany manner. In some embodiments, a data structure (e.g., a database) isused to store biases including, but not limited to, biased information,biased entities, and other biases. In some embodiments, the bias of thespeaker is able to be used to identify framing. For example, if aspeaker is known to be an ultra-conservative, that knowledge is able tobe used to label framing. In some embodiments, a comparison with otherpeople's take on a subject is used to determine spin. In someembodiments, the comparison is based on peers or groups. For example,news reporters are compared with other news reporters. In an example, if9 commentators label a speech as “well done,” and 1 commentator labelsthe speech as “poor,” the 1 commentator's comments are able to belabeled as “unrepresentative” or “minority view.” Further in theexample, the information that 9 commentators view something one way andthe 1 commentator views it another, is able to be used with additionalinformation (e.g., that the 1 commentator is an ultra-liberal), and the1 commentator's comment is labeled as “liberal spin.” In someembodiments, safeguards are able to be implemented to preventmanipulation such as a group ganging up against an individual.Additionally, the tone of the commentator, the number of factualinaccuracies by the commentator, and any other information is able to betaken into account to properly label the comments as spin, slant, biasor some other classification/category. In cases of subtle spin, such aswhere a commentator starts off by describing a radical element of agroup and then generally applies a broad stroke to the entire group,that is able to be detected as well. For example, antecedent basis ismonitored and checked. In an example, a commentator says, “the far rightis a bunch of warmongers,” and then later, the commentator says, “theright loves to go to war.” While the first statement may be true, thesecond statement is clearly an overly broad statement and is able to belabeled as “misleading” or is able to be clarified by adding “far” tothe statement to indicate “far right.” Entities including, but notlimited to, individuals, commentators, networks, companies and any otherentity are able to have labels or other information to help determine abias or slant. For example, commentators, channels, networks, websitesand blogs are able to be labeled with political terms or other terms asdescribed herein. Companies are able to be labeled with political termsas well or other terms including, but not limited to, anti-environment.Not only do the labels help identify to a viewer or reader where theinformation is coming from, but the labels are able to be quantified toperform additional calculations including, but not limited to,identifying spin. As described herein referring to the slant rating, thelabels are able to be determined using any data including, but notlimited to, the number of errors, types of errors, statistical analysis,surveys, analysis of content, analysis of past performance, and anyother information.

In some embodiments, the fact checker monitors a news story for bias orone-sidedness and presents helpful information to provide a full story.For example, if a news report discusses a police shooting of a suspectbut leaves out the aspect of the story that the suspect fired at thepolice first, the fact checker is able to determine the incompletenessof the story and provide supplemental information in any of the mannersdescribed herein (e.g., a text message of the missing information to theuser's mobile device, an alert that there is more to the story, anemail, or any other method). In an exemplary implementation, a databasewith full details of a story is maintained to compare with the presentedstory, and any information not mentioned in the presented story is ableto be supplemented. In some embodiments, the full detail database iscompiled by searching sources. In another example, if a news programonly discusses negative aspects about an issue, or if a news programonly discusses positive aspects about an issue, such one-sidedness isdetected. In some embodiments, to determine the one-sidedness, theunderlying data of the story is monitored (e.g., the stock market) andthe show/program is monitored, and then they are compared so that if theunderlying data changes but the show/program does not report the change,one-sidedness is detected. Furthering the example, if a show, for 3 daysin a row, mentions the stock market is down, and then the show issubsequently silent when the stock market is up for 4 days in a rowfollowing that, such a characterization is able to be detected. In someembodiments, the information is also presented to users (e.g., scrollingtext saying, “although this program mentioned the stock market beingdown 3 days, the stock market has been up 4 days since then”). In someembodiments, such information is able to be tracked and used to rate thenews program.

In some embodiments, a caller (e.g., of a radio show) or commenter(and/or his comments) is fact checked to determine the quality of thecaller/commenter. For example, the arguments of the caller areclassified as good/poor arguments, the grammar is classified, and otherinformation is taken into account to determine the quality of thecaller. Multiple callers are able to be analyzed to determine if thecallers are being selected to poorly represent one side of an argumentor a group of people. For example, if a radio show selects callers withoutrageous arguments for one side, and reasonable arguments for theother side, such a bias is able to be detected and indicated to users(e.g., listeners).

In some embodiments, supplemental information regarding what percentageof the population agrees or disagrees with a position is displayed. Forexample, a commenter says, “liberals believe in socialism,” and inresponse, an indication of “This view is shared by 20% of people whoconsider themselves ‘liberals’ and 5% of people who consider themselves‘democrats’ is shown.” In some embodiments, specific phrases aremonitored to implement this, such as “liberals believe” or “liberalsthink.”

In some embodiments, bias or other classifications are determined ortracked based solely on analyzing headlines, titles, or other headings.

In some embodiments, polling, ratings or other information are factchecked or analyzed for bias. For example, if a news organization saysthey cover stories with a fair representation of each side since theymentioned each side the same amount of time, further analysis is able tobe performed to determine if each time they had a bias towards one orthe other. And a clarification of bias is able to be presented. In someembodiments, a classification and an indication of sources, polling,organizations and/or other entities is presented. For example, if acommentator cites the XYZ poll, an indication that the XYZ poll is aleft-leaning poll is indicated.

In some embodiments, analysis and/or comparison of the fact checkingdata/results of networks, shows, web sites or other presenters of datais performed. For example, Channel A is found to lie (or err) 20times/day and have 1 stale story/day, and Channel B lies 5 times/day andhas 0 stale stories/day. Other data is able to be tracked including, butnot limited to, historical data and improvements or trends. The resultsand other information are able to be stored, sorted, compared, analyzed,searched, displayed (e.g., chart/graph/numerical), and/or used for manydifferent purposes. The information is also able to be used to generatea results rating. For example, channels are rated based on the number oferrors, number of corrections, timeliness of correction, number of stalestories, and/or any other factors. The results rating is able to be inany form including, but not limited to, 1-5 stars, A-F, 1-10 or 1-3diamonds. A slant rating is able to be used to indicate if a channel,show, site or other item has a political slant including, but notlimited to, liberal, conservative, moderate, or any others. Users arealso able to search, sort or perform other tasks based on the slantrating or other information. For example, users are able to set, sort orsearch channels, web pages, blogs, shows/programs and others, based onthe comparison of a results rating such as searching for all cable newsprograms with a 4 star rating or higher. The searches are able to begeneric or more detailed. For example, a user is able to search for allshows that have 3 stars or better. In an example of a specific search, auser searches for all shows with 4 stars or better, with a moderaterating, in channel range of channels 2-10.

Television/Video/Other Media

In some embodiments, archiving is implemented. For example, televisionshows are recorded or converted to text and recorded. In someembodiments, only fact checked aspects are archived. In someembodiments, only fact checked items that are classified a certain way(e.g., false) are archived. In some embodiments, the archives includegroupings. For example, false statements are in one group, hyperbole isin another group, and other items are in other groups.

In some embodiments, the fact checking is used for analysis ofcommercials. For example, if a law firm advertisement is displayed, thefact checker is able to provide statistics about the law firm including,but not limited to, where the attorneys went to law school, bar ratings,articles about the law firm, the law firm's website link, providecomparison results such as similar law firms and/or any other relevantinformation. In another example, a restaurant displays an advertisementthat is broadcast nationally, and the nearest location is able to bedisplayed by determining the user's location (e.g., the device locationvia GPS and/or IP address). Furthering the example, ratings, menus,nutritional information, allergen information and/or any otherinformation for the restaurant is made available or displayed. Againfurthering the example, a user's mobile device automatically mapsdirections to go to the nearest location from the user's currentlocation. In some embodiments, the fact checker is used to determine thevalidity of commercials. For example, if a commercial claims theadvertised product is the best, the fact checker is able to compare theproduct by searching for ratings on comparison websites, and/or anyother resources to determine if the commercial is true. The fact checkeris also able to present additional information to provide a user moredetail. For example, an automobile commercial claims the displayedvehicle is the #1 rated vehicle. The fact checker verifies the claim andalso informs the viewer that the vehicle is #1 rated for men ages 19-29,but overall, a competitor's vehicle is #1 rated. The fact checker isable to provide automatic comparison shopping. Any commercials oradvertisements are able to be fact checked including, but not limitedto, print, broadcast, digital/online and mobile-based. In someembodiments, a commercial or advertisement is detected based on aproduct, a company and/or language in the commercial/advertisement. Insome embodiments, a commercial/advertisement is detected using anotherimplementation.

In some embodiments, users are able to post comments directly to atelevised show or other video. For example, users send comments to atelevision network or show producer. In some embodiments, the networkfilters the comments. The comments are able to include citations provingor disproving a speaker's comment, or labeling the comment in anothermanner. As described herein, in some embodiments, comments are displayedto a designated group of users. In some embodiments, users are able tobe in more than one group.

In some embodiments, group video viewing is implemented. For example, aspecific group of users watch a video at the same time and are able topost comments and perform other fact checking aspects on the video.Users are able to invite others to join the group. In a further example,a set of co-workers form a viewing group to watch the State of the UnionAddress. While the State of the Union Address is displayed, the usersare able to input (e.g., tweet, instant message, text) comments aboutthe speech which are shown to the other users in the group. If theautomatic fact checker is implemented, then the speech is automaticallyfact checked as well. If the automatic fact checker is not implemented,users are able to flag items to be fact checked. Additionally, users areable to flag other users' comments, or users' comments are automaticallyfact checked, depending on the implementation. The groups are able to beas small as two people (e.g., husband and wife viewing the same videofrom different locations) or as large as an entire population (e.g.,billions). The groups are configurable in many ways. Users can be addedto groups, deleted from groups, be in multiple groups, and any othergrouping features are able to be implemented.

In some embodiments, television analysis is performed. For example, thefact checker monitors video and audio, converts the audio to text andanalyzes the text to provide information of what is going on in thevideo in real-time. The fact checking process is able to occur in thebackground, so that the user is able to view other channels. Bymonitoring and analyzing the video in the background, the fact checkeris able to then inform a user when it detects information the user islooking for. For example, there is a sports show on Channel 50 whichdiscusses all different sporting events such as baseball, golf, soccerand basketball, but the user simply wants a recap of golf scores. Theuser is able to input a search string (e.g., golf), or the systemautomatically knows what to look for based on previous searches or otherinformation (e.g., trending information), or another implementation isused to monitor. The fact checker analyzes the text of the show for theword “golf” or a related word/name/item such as par, U.S. Open, Tiger,and when the word is found, the user is alerted that his topic is beingdisplayed on that channel, so that the user knows to change to thatchannel. This enables users to avoid having to constantly switch backand forth to find a desired segment. In some embodiments, theinformation monitored is an actor, a location, and/or any otherinformation. In some embodiments, images are monitored (e.g., a userselects an image of an actor, and that image is compared with thebroadcast information to determine a match). In some embodiments, whenthe correct segment is being displayed, the channel automaticallychanges for the user. In some embodiments, a picture-in-picture windowof the other channel is displayed. In some embodiments, an audible orother alert is presented to inform the user. In some embodiments, thefact checker is able to be used to alert a user that a commercial isover, and that the desired show has returned. In some embodiments, thefact checker is used in conjunction with a recording device, forexample, a Digital Video Recorder (DVR) (e.g., TiVo®). After audio isconverted to text, a search is able to be performed on the text. Forexample, an entire sports show is recorded and converted. A search for“Tiger Woods” is performed by the user. The text is searched, and whenthe phrase “Tiger Woods” is found, the video begins playing from thatpoint in the video (e.g., in the video, a commentator mentions the name“Tiger Woods”). In some embodiments, every instance of the search phraseis found, so that the user is able to jump to each instance of thesearch phrase in the video. For example, if “Tiger Woods” is discussedat 5:59, 10:32 and 50:21 of the video, the user is able to hit a “Next”or “Previous” button to navigate to each point in the video where “TigerWoods” is mentioned. Any search techniques and/or features are able tobe implemented. In some embodiments, instead of a conversion of audio totext, text is provided in advance or during the show. For example,networks are able to provide text from the show in a searchable form. Insome embodiments, converted text or other text is also able to be usedto predict future television information. For example, a news programstates that stories about A, B and C will be shown tonight. The factchecker is able to determine when the specific stories of A, B and Cwill actually air, so that users are able to avoid stories they are notinterested in. The television analysis is also able to be applied toother forms of media including, but not limited to, radio, Internetwebcasts, videos and any other media. For example, the fact checker isable to monitor some or all radio stations for a desired song and whenthat song is found, the station switches to play that song. The searchis able to be used to find a song by a title, artist, based on severalwords of the song (e.g., first three words), or some other method.

In some embodiments, re-runs or replays of shows do not use additionalfact checking For example, if a show is typically displayed at 5 pm andthen replayed at 8 pm, the 8 pm show is able to use the previous factcheck information from the 5 pm show. In some embodiments, additionalinformation is provided in the 8 pm show that was not provided in the 5pm show. In some embodiments, analysis is performed to confirm the showsare the same.

In some embodiments, the fact checking is performed using an originalbroadcast and then displayed during a repeat broadcast or a recordedbroadcast. In this implementation, the fact checking is able to be inreal-time or non-real-time, automatically or not automatically. Forexample, a show is broadcast at 5 pm, and fact checking occurs. Then,when the show is re-broadcast at 8 pm, fact checking results/informationis presented automatically and in real-time during the re-broadcast.Similarly, when a re-broadcast occurs via the Internet, such as on abroadcaster's website, results/information is presented during there-broadcast. Although this would not prevent misinformation from beingspread in the initial broadcast, the fact that any re-broadcasts wouldcatch any misinformation could potentially discourage misinformationfrom being presented in the initial broadcast. In an exemplary manualimplementation, viewers watching the 5 pm telecast flag information asmisleading, incorrect, unclear and/or any other characterization, thenfact checking and/or other analysis is performed, and then at a latertelecast (e.g., the 8 pm telecast), corrective and/or supplementalinformation is displayed automatically to the viewers of the latertelecast at the appropriate times. The appropriate times are able to bedetermined in any manner, including, but not limited to, monitoring forkeywords (e.g., database includes keywords to monitor and correspondingcorrective comments to display), monitoring for a designated time (e.g.,each time a user flags information, a timestamp is made which is thenused to display the corrective comments) and/or any other method.

In some embodiments, polling occurs during a broadcast and then isposted during the re-airing of the show. For example, a poll ispresented, “conservatives, do you agree with Commentator A's position,”and people respond, and then the results are shown that “earlier pollsshow X % polled agree with this position.”

In some embodiments, the fact checking system is used to avoid orcorrect a mistake presented. For example, in the past, news networkshave accidentally posted graphics with incorrect statistics. The factchecking system is able to preemptively check the graphics orpost-display check the graphics, so that the poster (e.g., network) isable to correct the error before broadcasting the error or quicklythereafter.

In some embodiments, automatic prediction tracking is implemented. Forexample, a commentator says, “President Z is going to lose in 2012.”That comment is stored, and once a result is determined (e.g., theelection ends), the accuracy of the prediction is determined (e.g.,using the fact checker). In some embodiments, the predictiondeterminations are stored, used for statistics, to generate predictionratings/accuracy ratings and/or for any other purposes. For example,commentators or any other entities that make predictions are able tohave prediction ratings so that viewers are able to see how accuratecommentator's predictions are. For example, when a commentator is shownon television, a prediction rating is shown (e.g. correct predictions 5,incorrect predictions 10) to indicate to viewers that this commentator'spredictions do not usually come true. The prediction ratings are able tobe in any form such as grades (A-F) or any other rating scheme. In someembodiments, multiple categories of predictions ratings per entity areimplemented. For example, a sports analyst may predict football well butnot baseball, so his rating for football is high but for baseball islow. Examples of entities that make predictions, guesses or estimatesinclude but are not limited to, commentators, weathermen, stockcommentators, news commentators, businesses, sports commentators, realestate commentators, analysts, financial commentators, entertainmentcommentators, reality show hosts/judges, and/or any other entity.

In some embodiments, the fact checking system is used to rate weatherpredictors. For example, if one channel is wrong more often thananother, viewers would be informed of this and could change theirviewing habits accordingly. In some embodiments, viewers are given alist of alternatives. For example, a list of channels with accuracypercentages is displayed.

In some embodiments, a stock picker is fact checked to determine theaccuracy of stock pickers. For example, if an online site boasts aboutbeing able to select stocks, the fact checker is able to monitor thepicked stocks and then provide an accuracy rating for the site, so thatusers are able to use the most accurate site. Similarly, sports analystsare fact checked and tracked to indicate the accuracy of the sportsanalysts' predictions/picks.

In some embodiments, the fact checker indicates a status of a comment tothe host/interviewer of a show (e.g. so that the host is able to ask afollow-up question). In some embodiments, the fact checker comes up withthe follow-up question automatically (e.g. follow up question isdisplayed on teleprompter). For example, if a host asks a guest what theguest does not like about the President, and the guest responds that“taxes are too high.” The fact checker is able to determine that thecurrent President has lowered taxes since becoming President, andautomatically generate a follow-up question of, “since the President haslowered taxes, is that a valid complaint about the President?” In someembodiments, the follow-up question is based on searches performed bythe fact checker. In some embodiments, a database of potential follow-upquestions is implemented and based on the answer, a follow-up questionis selected.

In some embodiments, an avatar or other representation of an entity isdisplayed on a show (e.g., a television show or webcast) to present thefact checking information. For example, a political commentary show hasguests, and one of the guests is able to be an avatar that comments whenone of the other guests or the host makes a misstatement or some otherstatement that warrants commenting. The avatar is able to becomputer-generated or any other type of generated avatar.

In some embodiments, the severity (e.g., severity of incorrectness,severity of bias, severity of political slant) of a statement isindicated with the result. For example, if a person says, “Rhode Islandis the largest state,” a severity rating of 10 is displayed as thestatement is completely wrong since Rhode Island is the smallest state.In another example, if a person shows extreme bias, a bias severityrating of 10 is displayed. The severity rating is able to be indicatedin any manner, including, but not limited to, 1-10, by grades including,but not limited to A-F, bright colors indicating severe and dull colorsindicating not severe, imagery/pictures, audio (e.g., “wow!” for severe,“wah wah” for not severe, or a loud chime for severe, a quiet chime forless severe), or any other rating, grading or indicating system.

In some embodiments, the fact checker is used to inform a person (e.g.,a host) that he made a mistake. For example, a host states the U.S. is$15 Billion in debt, and a chime and/or other audio is emitted in thehost's earpiece, letting the host know that he made a mistake. In someembodiments, the chime is merely just a short chime where the host hasto figure out what the mistake was, and in some embodiments, the audiois a correction (e.g., “Trillion” in this example) or a chime linked toa teleprompter that could display accurate information or incorrectstatement. In some embodiments, the indicator to the person is visual(e.g., a flashing red light), tactile (e.g., vibration), or any otherindicator.

In some embodiments, a host, guest or other entity is providedadditional information (e.g., statistics) by the fact checker during acommunication. In some embodiments, additional information is indicatedwhen questionable information or other information is presented. Forexample, in a debate, debater A is able to have the fact checker runningwhile debater B is making comments. Debater A is then able to use thefact checked information to debate better.

In some embodiments, using the fact checker, if a commentator (e.g.,guest) is found to have misstated facts a specified number of times(e.g., 3 times) within a specified period of time, an action isautomatically taken against the guest (e.g., the guest's microphone iscut off for a period of time). For example, a guest is on a politicalcommentary show, and he makes 3 factually inaccurate statements on theshow, his microphone is cut off (silenced) for 1 minute. In addition tofact checking, other events are able to contribute towards taking theaction. For example, if a guest keeps interrupting other guests, eachinterruption could contribute toward taking action. For example, a guestinterrupts once and makes two factually inaccurate statements; those 3events cause the action to be taken against the guest. Another exampleof an action is shining a colored light (e.g., a red light) on theentity for a period of time. In another example, when a score ismaintained to determine the winner of the argument on the show, anaction includes disqualifying a participant or deducting points due toimproper conduct. The action is able to be taken against any entity, notonly a guest, and any actions are able to be taken.

In some embodiments, points are awarded to hosts, guests,callers/commenters and/or others based on their arguments to determinewho wins an argument. The points are able to be awarded based one ormore factors including, but not limited to, factual accuracy/inaccuracyof the arguments, conduct, viewer voting, judge voting, and/or any otherfactors. The point tally is able to be kept running while the argumentoccurs and/or indicated at the end of the argument. For example, apolitical commentary show includes a segment with a host debating aguest on a controversial topic. The host and the guest each go back andforth presenting their arguments. The fact checker automaticallymonitors, processes, and fact checks the arguments and then gives pointsfor factually accurate information, and deducts points for inaccurateinformation. The fact checker also determines if improper conductoccurs, for example, cutting off the other or filibustering (e.g., notanswering the question directly), and deducts accordingly. While thesegment is airing, or quickly thereafter, users are able to vote (e.g.,by text or any other implementation) for who is winning/won theargument. A formula is able to be implemented to add the votes with thefact checker results to determine a score (e.g. whoever wins eachargument receives a point which is added to the fact checker points).Then at the end of the segment or some other point in the show, theresults are displayed, indicating a winner of the argument (e.g., theone with the most points). In some embodiments, a host is given ahandicap (e.g., host starts with a 1 point reduction) in an attempt tobalance the likely bias of his viewers. In some embodiments, users areable to select the factors used in determining a winner. For example, ifa user does not like the idea of other users affecting the outcome, theuser is able to specify that the winner is determined solely based onthe fact checker results.

In some embodiments, when an entity communicates (e.g., speaks orwrites) or is displayed, donors and/or contributors who have contributedto him or his campaign and/or charities or other entities he hascontributed to are displayed. For example, a politician is shown ontelevision, and a list of the top 10 contributors to his campaign isdisplayed on a user's mobile device. In some embodiments, onlycontributors related to a topic (e.g., discussing energy, display oilcompany contributions). Any amount of information about the contributorsis able to be displayed (e.g., how much in contributions, when thecontributions were made, and other information). The contributioninformation is able to be determined using a data structure (e.g. adatabase) which stores entities and related contribution information,via searching as described herein or any other method.

In some embodiments, a list of names of supporters and/or dissenters ofinformation is presented. The list is stored in a data structure such asa database and/or is based on previous comments, writings and/or otherinformation. For example, a guest on a talk show makes the comment:“lower taxes creates jobs,” and a list of prominent people supportingthat position is displayed.

In some embodiments, the fact checker is used to assist users in readingthe fine print displayed in television advertisements. For example, thefact checker captures the fine print and allows the reader to displaythe fine print for longer than the normal display time. In anotherexample, the fact checker allows the user to capture and enlarge thefine print so that it is more legible.

In some embodiments, to determine a character/actor/location/otherinformation, a user takes a picture of a television screen, computerscreen, mobile device screen or any other object/scene. For example, ifa movie is being played on a person's television, the person uses hismobile device to take a picture of the screen, and then the mobiledevice is able to analyze the picture and determine the actor, moviebeing played, where the set location is, and/or provide any otherinformation.

In some embodiments, when a poll is referred to, related polls aresearched for and presented. In some embodiments, the polls are compared.For example, Political Program X only shows an XYZ poll that showsCandidate Z in the lead, but a similar poll (ZZZ poll) shows Candidate Yin the lead, then the ZZZ poll is also presented. Similar polls are ableto be searched for in any manner, including, but not limited to, same orsimilar dates, same or similar topics and/or any other manner.

In some embodiments, a mobile device (e.g. smart phone) is used to scana television advertisement to obtain information. For example, if a useris watching television and a commercial appears, the user holds hismobile device with camera so that the camera is able to scan thecommercial, and then the user is able to click on an item in theadvertisement or entire advertisement to receive additional informationregarding the item and/or advertisement. In some embodiments, the useris able to transfer the advertisement to his mobile device (e.g. bypointing the camera of the mobile device at the advertisement andselecting “transfer” or “capture”).

In some embodiments, fact check information and/or supplementalinformation is indicated while a user is fast-forwarding, pausing and/ortaking another action with a video. For example, while a user isfast-forwarding a DVD, supplemental information is displayed to theuser.

In some embodiments, a DVR records a show with or without fact checkedinformation or supplemental information, but fact checked informationand/or supplemental information is determined in the time between theinitial recording of the show by the DVR and when the user views therecorded information, so that when a user views the recordedinformation, the fact checked results and/or supplemental information isdisplayed. In some embodiments, the fact checked results and/orsupplemental information is stored on the DVR, and in some embodiments,the information is stored on another device. In some embodiments, thefact checked results and/or supplemental information is updatedincrementally as new information is determined.

In some embodiments, supplemental information that includes a fusion ofgenres is implemented. For example, a user is watching a politicalcommentary show and comedic supplemental information is provided. Thedetermination of the supplemental information to provide is the same asor similar to other implementations described herein. In someembodiments, a database of keywords and corresponding actions to take orinformation to display is maintained, or the actions or information arebased on searches performed. For example, a database includes a keyword“global warming” and a joke related to global warming is included tocorrespond with that keyword. Then, as the information is monitored, andthe keyword is detected, the joke is presented to the user (e.g. on hismobile device or television). In some embodiments, more information isused in determining what supplemental information is displayed. Forexample, user-related information is used including, but not limited to,age, gender, location, political leaning, and any other information.Furthering the example, if a user is conservative, a joke linked toglobal warming would be critical of global warming; whereas, a joke fora liberal user would be critical of those who do not believe in globalwarming.

In some embodiments, a personalized viewing schedule is implemented. Thepersonalized viewing schedule is able to be implemented by switchingamong channels, using a video recording system (e.g. DVR or TiVo®),using online video, using radio and/or any other implementation. Forexample, after the fact checker monitors and processes a 10 pm newsprogram, in conjunction with a DVR storing the news program, the factchecker displays a list of topics/stories covered in the news program.Furthering the example, the 10 pm news includes a stock market report, ahomicide report, a weather report, a sports report, and a story aboutlocal art projects. The user is presented these items (e.g. in a list),and then the user is able to select and/or rank the stories to watch inorder or select only particular stories to view. For example, the userchooses to watch the sports report, the stock market report and theweather report, and then only those stories are shown to the user. Insome embodiments, the items (or segments) are pre-sorted based onprevious selections by the user, user preferences, friends' selections(e.g. Facebook contact recommendations), popularity, and/or any otherbases. In some embodiments, the list of stories is displayed on thescreen, so that the user is able to see what stories are upcoming.

In some embodiments, the fact check information and/or supplementalinformation is displayed as part of and/or during a commercial break.

In some embodiments, a fact checker button is implemented for turningon/off the fact checking system. The fact checker button is able to belocated on a remote control, television, mobile device and/or any otherdevice and is able to be a hard button, soft key, menu selection, or anyother implementation.

In some embodiments, the fact checker is implemented such that themonitoring, processing, and fact checking are performed automatically,but a user (e.g. moderator) is also involved with the indicating suchthat it is performed semi-automatically. For example, a person's speechis monitored, processed and fact checked automatically, and then theresults of the fact check are displayed to a moderator who is able todetermine which fact check results are indicated (e.g. displayed toviewers). For further example, the fact checker finds that the speakermisspoke and said $100 Billion instead of $100 Million. The fact checkerpresents this to the moderator who then approves the correction which isthen posted to viewer's screens. Although this slows down the processslightly, the delay will be minimal such that the indication is stillpresented within several seconds and possibly even within one second.

Additional Structure and Execution

In some embodiments, a device such as a mobile device is used to performa fact check of an item through the use of the device's camera or othersensor. The mobile device is able to scan (e.g. merely point camerawithout taking picture), take a picture, take a video, or any othermethod of acquiring the content of the item. For example, a mobile phoneis used to take a picture of a print newspaper and perform a fact checkof the newspaper. The writers of the articles are able to be rated asdescribed herein. The newspaper or magazine is able to be rated asdescribed herein. For example, tabloids are viewed as unreliable or aregiven less credibility than a standard newspaper. Any print material isable to be fact checked, including, but not limited to, newspapers,magazines, books, billboards and pamphlets, including any advertisementswithin. In some embodiments, the device is able to fact check an itemincluding, but not limited to, a purse, dress, watch, ring, shoe, suit,clothing, or any other item to determine the brand of the item and/or ifthe item is a replica. For example, a user directs the camera of hismobile phone toward a watch and the fact checker determines if the watchis an original Rolex or a replica. The fact checker is able to performthe check in any manner such as determining that the watch says Molexinstead of Rolex, or by a picture comparison of the acquired watch andcertified watches stored in a database, comparing distinct features of agenuine article such as stitching and/or hardware/material used, or anyother comparison.

In some embodiments, the item determination is performed on items ontelevision, the Internet or elsewhere. For example, during an awardsshow, the item determination posts information about the dresses beingworn, including, but not limited to, designer and/or price. The factchecker is also able to perform person identification. Using the awardsshow example, an indication of who is being shown on camera is able tobe displayed. As described herein, facial/body analysis or any othermethod is able to be performed to determine who people are.Additionally, character/actor/person determination is able to beperformed. For example, if a commercial is being displayed, and a useris curious who the main actor is, actor determination is implemented todisplay the actor's information. In some embodiments, allcharacter/actor information is displayed, only selected character/actorinformation is displayed, or any other configuration of information isdisplayed. For example, all names of actors on a television show areshown under each actor. In another example, a user specifically selects(e.g. by touchscreen or any other method of selecting) the actor to seeinformation. The amount of information is also able to be variable. Forexample, as little as a name is shown or much more detailed informationis shown including, but not limited to, biographical information, othershows/movies, ratings/reviews, links, character/plot summary (e.g. asummary of this character's involvement in the plot) and any otherinformation. In some embodiments, information about when a specifiedactor will be on television next is displayed. For example, a userclicks on Actor A, and the user is informed that the actor is also inMovie Z, at 7 pm on Channel 263. For sports, some or all names of theplayers are shown on/near each player. In another example, a userspecifically selects (e.g. by touchscreen or any other method ofselecting) the player to see information. The amount of information isalso able to be variable (e.g. game stats, historical stats, personalinformation, fantasy football stats, and any other information). Thefact checker is also able to perform location recognition. For example,if a reporter is “on location,” the fact checker is able to determinewhere that location is. The fact checker is able to determine thelocation by comparing the image with a stored image, by searching thecredits (e.g. a movie specifies locations of shootings), by searchingtext of the transcript (e.g. newscaster earlier said, “we're on locationlive at x,” and/or any other implementation. In some embodiments, aftera location is determined, the viewer is able to pull up additionalinformation about the location (e.g. historical information, currentinformation (weather, prices of goods)). Character determination,location determination and any other determination is able to beimplemented using any media including, but not limited to, television,movies, photographs (e.g. online photographs), videos (e.g. onlinevideos), satellite information, prior news feeds, or any other media. Insome embodiments, identifying the object is by comparing the object withother objects in the scene, finding a story/article about the object, orany other method of identification. Distances and/or sizes of objectswithin the scene are able to be determined with scene analysis.

In some embodiments, the fact checker checks for and indicatesdefamation, slander, libel, plagiarism, copyright infringement,trademark infringement, patent infringement, and/or other crimes. Insome embodiments, when a crime is committed or may have been committed,the targeted person and/or someone else (e.g. the police) is contacted(e.g. an email or Tweet is sent with the criminal comment, whosaid/wrote the comment, and any other relevant information). In someembodiments, defamation or other crimes are determined by: determiningthe location of the speaker or victim, determining if the statement isfalse, determining state law and presenting the state law and statementto the victim or the victim's attorney and/or analyzing the law todetermine if the law is violated. In some embodiments, additionalelements are considered such as defenses to the crime. In someembodiments, other crimes/laws are fact checked by analyzing thelaw/statute/regulation/ordinance/cases/other information, analyzing thefacts and determining a result. In some embodiments, a database of laws,cases and holdings is used to perform the analysis. In some embodiments,the analysis merely returns similar cases, so that the user is able tocompare. In a same or similar manner, a disparaging comment is detectedand reported (e.g. to the target of the comment). For example, ifsomeone writes on a message board that Company XYZ is a terriblecompany, the comment, web address, citation, and/or any otherinformation is sent (e.g. by email, Twitter or any other means) to thetarget of the comment.

In some embodiments, future shows and/or news stories are based on factchecking results. For example, if users respond to news stories asoverplayed, future newscasts will not include stories related to thattopic. In another example, if users request more information about anaspect of the story (e.g. victim's race), future newscasts will includethat information. In another example, if users rate a story as “biased,”the future newscast will remove the bias.

In some embodiments, an indication on or near a headline, title,caption, talking point and/or other short phrase is implemented. Forexample, a rating of a story, article, news or any other information isable to be implemented. In some embodiments, the rating of the story isbased on an automatic fact check of the story. In a further example, atitle of an article is “Vaccines Proven Harmful,” but the article usesstudies that have been discredited and readers rate the article poorly,future viewers will see the article as “Vaccines Proven Harmful 0Stars.” In some embodiments, the indication is not near the headline orother phrase. For example, the indication is on a user's mobile deviceafter scanning or taking a picture of a hardcopy title. In someembodiments, the indication is a characterization of the article. Forexample, the article is characterized as liberal, neutral orconservative. Other characterizations, ratings and indications are ableto be implemented. In some embodiments, an indication of a better and/oropposing article, story and/or other information is indicated. In someembodiments, if a headline is determined to be misleading (e.g. bycomparing the headline with the content of the article and/or based onuser reviews), an indication of “misleading” is displayed near theheadline.

In some embodiments, stories (e.g. articles, news stories, and other)are rated. For example, if users are tired of hearing about Story X,users are able to communicate that opinion. In some embodiments,broadcasters and/or reporters are able to receive the ratingsinformation automatically, so that they are able to cut short, extend orotherwise modify the programming. In some embodiments, users are able toprovide more specifics about the rating of the story. For example, aviewer is able to indicate she is tired of the slanted presentation ofthe story or the presentation of the lineup of stories (e.g. alwaysmaking criminals looking like they were unfairly treated by leaving outimportant details). The ratings are able to be any form of ratingsincluding, but not limited to, thumbs up/down, good/bad, 1-10, A-F,emoticons, a selection from a list of choices, and/or any otherimplementation.

In some embodiments, a self-checking system is implemented. For example,a mobile device application including, but not limited to, an iPhone®App, monitors a person's comments when he speaks, and if the person sayssomething incorrect, the application alerts (e.g. chime, ringtone) theperson. For further example, a dad is explaining geography to hisdaughter and says Alabama is West of Mississippi; the applicationchimes. In some embodiments, the application provides a correction,provides a citation and/or any other information to help the person. Insome embodiments, the self-checking is able to be implemented to providepositive feedback for saying a correct statement, for example, as alearning tool or a game for children. In some embodiments, a quiz, amultiple choice program, or other testing material is implemented. Insome embodiments, the fact checker fact checks a user's statement andthen asks a question related to the statement. In some embodiments, thefact checker learns based on the result of the fact check to ask anadditional question. In some embodiments, based on a series ofstatements by the user, the fact checker asks the user a question. Insome embodiments, the self-checking system has the ability to only factcheck a specified user (e.g. by voice recognition or some otherrecognition) so that other people's comments are not fact checked. Forexample, if a user implements a self-checking iPhone® application whichmonitors everything received by the iPhone® listening device, then whilethe user is walking on the street, conversations of others may be factchecked. If the user does not want these other conversations factchecked, the specified user implementation is able to filter receivedinformation, and only fact check statements made by the specified user.

In some embodiments, the fact checking is implemented in or as a searchengine and/or a browser. Using a standard search engine, entering astatement such as “Alaska is the largest state” results in links beingdisplayed on the screen which enable a user to then select a link wherethe user is able to verify if Alaska is the largest state. Using a factchecking enabled search engine, a user is able to enter “Alaska is thelargest state” in the browser window, and the result of “True” appears.In some embodiments, links still appear as from a standard searchengine, and next to or near each link appears a result including, butnot limited to, True/False or any other indicators. In some embodiments,search engine capabilities are available in other software (e.g. wordprocessors) to perform a fact check.

In some embodiments, the fact checking system is embedded or used with aword processor including, but not limited to, Microsoft® Word or anyother software program. In some embodiments, the word processorhighlights, underlines, circles, auto-corrects or performs another formof fact checking identification. In some embodiments, if the statementbeing fact checked could be corrected in more than one way, a user ispresented with multiple options. For example, if a user types, “Texas isthe biggest state,” the user is able to be presented with “Alaska” as areplacement of Texas, or “second biggest state,” to clarify that Texasis the second biggest state.

In some embodiments, the fact checker is implemented as part of anoperating system.

In some embodiments, some or every tweet a person sends out ishighlighted or color-coded based on the type of tweet. For example,different tweets are coded as factually correct, factually incorrect,spin, opinion, hyperbole, or any other characterization.

In some embodiments, email is fact checked. Depending on the embodiment,the email is fact checked before being sent out or fact checked when theemail arrives in a user's inbox, or when the user opens the email. Insome embodiments, when the user opens the email, the email is able to beprovided marked up such that factually inaccurate statements areindicated, for example. In some embodiments, a user is able to send theemail to a service, and the service returns a marked up version. Theservice is able to be local to the device (e.g. software running on auser's device) or could be external including, but not limited to, onthe Web. The same or similar implementations are able to be used for SMStexts, MMS texts, audio texts, or any other communication. In someembodiments, an entire email or other message is indicated as “spam” orany other indication/label if it is found to be factually inaccurate. Insome embodiments, a threshold is implemented to determine if the messageis spam. For example, if the threshold is 10 inaccuracies, and 11factually inaccurate items are found, then the message is labeled asspam.

In some embodiments, conversations are recorded for a time period (e.g.a night) so that they are able to be used later for comparison with astatement.

In some embodiments, a closed system of information is searchable, suchas for a court case. For example, all documents, testimony and evidenceare put in a searchable digital format, and if someone makes aconflicting statement compared to what is on the record, an alert or asimilar effect is presented. In some embodiments, all of the searchableinformation is fact checked. In some embodiments, the fact checkerperforms a document reviewer's task. In some embodiments, legalarguments are fact checked to make sure a case is not cited out ofcontext, a holding is not misstated, and/or any other checking.

In some embodiments, a language translator is implemented. For example,a video is translated from one language to another using closed caption.In another example, only mistakes are translated and displayed. In someembodiments, a foreign language monitor is implemented. For example, ifa device knows a user's native language is English, and the user isattempting to speak Spanish, the device monitors for incorrect usage orpronunciation. In some embodiments, the device monitors every languagefor incorrect usage or pronunciation. For example, if a user says, “youplayed good today,” the device is able to correct the user and indicatethe sentence should have been, “you played well today.” In someembodiments, the fact checker checks for outdated word use.

In some embodiments, if a comment is made about an individual, a group,a company or any other entity, that person is able to post a commentrebutting the comment on a different location than the original comment.Or the rebuttal is on the person's website and pulled, or tweeted,spoken, or any other means. For example, if Person A says Person B plansto raise taxes, the fact checking system is able to pull a quote fromPerson B's website that says, “I promise not to raise taxes,” and thatcomment is automatically posted with Person A's comment, providing areal-time rebuttal. The rebuttal is able to be made/posted before theopposing comment is made for an immediate rebuttal. The location of therebuttal is able to be found in any manner such as by determining thename of the person being commented on and finding the person's personalwebsite (e.g. Facebook® page).

In some embodiments, the fact checker is used to prevent bullying onsocial networking sites including, but not limited to, Facebook®,Myspace, LinkedIn, Twitter, and other websites. For example, users areable to flag other poster's comments or pages as false or any othercharacterization. Additionally, as described above, an automaticrebuttal is able to be implemented such that if a user posts somethingon his site and then other users post a contradictory remark on theirsites, the user's post is automatically used to rebut the other users'comments. For example, if a group of users try to disseminate a rumorabout Teen X, Teen X is able to post a remark on his page that the rumoris not true. Then, when the group of users post their rumor on theirsites, their comments will be marked on their sites, and they will berebutted immediately, helping to dispel the rumor. The user is able topost his rebuttal proactively or after the other remarks are alreadymade.

In some embodiments, real estate prices/values are fact checked. Forexample, if a real estate agent tells a person, “this house is worth$500,000” the fact checking system is able to take data regarding thehouse and do a real-time comparison with comparable sales (and otherfactors or specific information related to the house or the purchaseincluding, but not limited to, household incomes, unemployment rates,population growth, upgrades, and others) and determine the validity ofthe agent's price. Other price comparison is able to be performed aswell such as with tradespeople. For example, if a plumber quotes aperson $100 to replace a pipe, the fact checking system is able todetermine what other plumbers in the area charge for such a task and/orcompare BBB ratings. In some embodiments, a rent checker is implemented.In some embodiments, other price comparison is performed including, butnot limited to, comparison of stores, online goods/services or any othergoods/services.

In an example of live fact checking, while a sporting event is beingbroadcast, a commentator provides commentary including statistics whichare usually fed to the commentator by someone behind the scenes. Tofurther ensure the accuracy of the comments, the fact checker is able tobe implemented to monitor the data fed to the commentator before thecommentator presents it or after the commentator makes the statement, sothat he is able to make any corrections.

In some embodiments, a picture-in-picture configuration is used toprovide information and results from the fact checking system to a user.In some embodiments, picture-in-picture is not used.

In some embodiments, the fact checking system is used to fact checkarchived data. For example, a network's past footage is fact checked.The results of the archived data are able to be used in rating thenetwork or for other purposes.

In some embodiments, hypocrisy is detected. For example, statements arecompared to source information to determine if previous statementscontradict or are hypocritical. For example, Speaker A says, “we shoulddo X” and then two weeks later, Speaker A says, “we should not do X,”the second statement is indicated as hypocritical or flip-flopping. Insome embodiments, the first statement is then displayed. Context is ableto be implemented in conjunction with searching for hypocriticalstatements. For example, if Speaker A says, “adultery is wrong,” butsources show that Speaker A previously committed adultery, an indicationthat Speaker A is being hypocritical is presented. Any other methods ofdetermining hypocrisy are able to be implemented. Further, hypocrisy isable to be included with the validity rating of entities describedherein. For example, when Speaker A appears on a television program, alabel of hypocrite and/or a number of hypocritical statements/actions ispresented. In some embodiments, dates or time frames are used indetermining the relevance of fact check comparison. For example, if ahypocritical statement was made 30 years ago, the fact checker mayrealize that it was more likely a change of view rather than ahypocritical statement; whereas, a contradictory statement made 2 weeksago is likely due to hypocrisy not a change of view. In someembodiments, items similar to hypocrisy including, but not limited to,flip-flopping and waffling are detected. In some embodiments, dates ofwhen the conflicting (e.g. hypocritical) statements/actions occurred aredisplayed. Contradictions and other similar items are able to bedetermined in any manner, including, but not limited to, logiccomparisons. For example, sentences with and without “not” are compared.In another example, detecting antonyms is used. In another example, adata structure (e.g. database) of quotes is kept and the quotes areclassified (e.g. pro-tax), and if quotes by the same entity are onopposite classifications, hypocrisy is determined. Furthering theexample, a commentator says we should attack Country A, which isclassified as pro-war with Country A, and then later the commentatorsays we should not attack Country A, which is classified in an opposingcell as anti-war with Country A, hypocrisy is detected and indicated. Insome embodiments, a database of potentially hypocriticalstatements/actions is maintained and monitored for contradictions. Forexample, the database includes names/entities and correspondingstatements that are most ripe for hypocrisy (e.g. positions on adultery,wasting money, other political positions).

In some embodiments, subscriptions are implemented. Subscriptions areable to be implemented to perform any variety of subscription services.For example, users are able to subscribe to or unsubscribe to factchecking being displayed on their television screen. In someembodiments, users are able to subscribe to different levels of factchecking. In some embodiments, users are able to select preferencesand/or settings for the extent of or quantity of items to be factchecked.

In some embodiments, the fact checker is used with rating websitesincluding, but not limited to, yelp.com to ensure the comments/reviewsby users are accurate. For example, if a user states that Business X isthe worst in State Z, but Business X is not even in State Z, the commentis able to be filtered.

In some embodiments, the fact checker is used for fact checking sports'rules and the implementation of the rules. For example, the fact checkeris used for determining if the umpire/referee made the correct call. Thefact checker is able to analyze video or images of the sport, determinethe applicable rule, analyze the facts and the rule, and produce ajudgment.

In some embodiments, the fact checker is used to fact check personalinformation. For example, a potential employer uses the fact checker tofact check potential employees' resumes. The fact checker is able totake portions of the person's resume and compare the person's educationwith education records, previous job history with company information,Bar information with public legal databases, and any other information.In another example, a mortgage company uses the fact checker to factcheck a potential borrower's mortgage application. In yet anotherexample, a dating service uses the fact checker to fact check people'spostings. In another example, health information is checked, and toverify that a person qualifies for life insurance, the person'sapplication is fact checked based on medical records. The fact checkeris able to be used based solely on what is in a person's document (e.g.resume) or based on other information as well. For example, in someembodiments, a person's name is able to be used to locate supplementalinformation regarding the person. For example, the person's web page,Facebook® page, previous papers/articles written and any otherinformation is able to be found to supplement the information provided.In some embodiments, only public information is searched, in someembodiments, only private information is searched, and in someembodiments, both public and private information is searched.

In some embodiments, the fact checker is able to be used to providedetails regarding a physical object. For example, if a user takes apicture of a painted wall, the fact checker is able to determine thecolor, brand, type and/or any other information about the paint bydatabase, based on date, location and any other information. In anotherexample, the physical object determination is able to be used forlearning, such that a person is able to take a picture of an object andthe fact checker provides information about the object. For example, achild takes a picture of a cat, and the fact checker tells the childthat it is a cat and that the cat is gray. In some embodiments,additional information is provided including, but not limited to,history of cats, anatomy of cats, and any other information. In someembodiments, the user takes a picture and then inputs (e.g. voice input)what the user thinks the object is, then the fact checker determines ifthe user is correct. For example, a child takes a picture of a cat andsays, “dog,” the fact checker will determine that the object is a catand inform the user of that he is wrong and/or provide the correctanswer. In some embodiments, a game is played using the fact checkerwhere after the user takes the picture, the fact checker asks a questionabout the object. For example, a child takes a picture of the cat, and aquestion of what color the cat is, is presented. The fact checker thenanalyzes the response and responds accordingly. More difficult questionsare able to be asked as well, such as historical questions (e.g. whichgroup worshipped cats?), geography questions (e.g. what country has themost cats?), and/or mathematical questions (e.g. how many trees do yousee in this scene?). In some embodiments, the questions becomeprogressively more difficult as the user answers correctly. In someembodiments, the information acquired when taking pictures is organizedin a report format. For example, if a student is supposed to do a reporton different types of trees, and the student takes pictures of 5different trees, a report, including the pictures, is generated withdetails about the trees. In some embodiments, the user is able to take apicture of a food item, and recipes are generated that use that item. Insome embodiments, the user is able to take a picture of a store (e.g.restaurant), and information about that store is presented including,but not limited to, user ratings/reviews, critic ratings/reviews, hoursof operation, menu and/or a description of the store. In someembodiments, the user does not have to take a picture; rather, the usermerely points the lens of the camera of the mobile device at the object,and the device is able to scan the object. The information providedabout the object is able to be based on a database lookup, a search orany other implementation. In some embodiments, the user takes a pictureor points the camera at a street sign, and a list of items (e.g.restaurants) is displayed in order of proximity, ratings and/or reviews,for example. In some embodiments, GPS or another locating mechanism isused for determining a user's location.

In some embodiments, users are given rewards, awards and/or prizes forparticipating with and/or contributing to the fact checker.

In some embodiments, a collection of incorrect predictions and/orstatements and/or hypocrisy is maintained.

In some embodiments, a shortcut fact checker is implemented. Theshortcut fact checker performs a shortcut fact check and indicates“likely true,” “likely false” or another indication. The shortcut factcheck is implemented by performing a search and based on the number ofresults, indicating “likely true” or “likely false.” For example, if asearch results in zero results or few results, “likely false” isindicated. If a search results in many results, “likely true” isindicated. In some embodiments, the shortcut fact checker usesreliability ratings to narrow sources used. In some embodiments, theresult accuracy rating is used (e.g. only “likely true” if there aremany results with an accuracy rating above a threshold).

In some embodiments, the fact checker is implemented to correct wordpronunciation of any communication (e.g. of broadcast information). Forexample, people's names, geographic locations and any other words areable to be corrected. In some embodiments, the fact checker compares thesound clip with another sound clip. For example, a database of people'snames is stored and when their name is spoken, the pronunciation iscompared with the stored data in the database. For example, each playeron a football team says his name, and it is recorded in a database,then, when a broadcaster says his name, if it is mispronounced, someform of action is taken including, but not limited to, playing thecorrect version to the user, playing the correct version to thebroadcaster so that he is able to repeat it, playing a chime to thebroadcaster, displaying a phonetic spelling to the users and/or thebroadcaster, and/or any other indication. In some embodiments, the soundclip is converted into text, and then the text is compared with apronunciation guide. In some embodiments, the fact checker isimplemented to correct grammar of any communication (e.g. of broadcastinformation). For example, if a commentator says, “I'm doing good,” thegrammar correction is able to correct the statement by indicating, “I'mdoing well.” The indication is able to be any indication; for example,sending a corrective Tweet to a user's mobile device.

In some embodiments, a lie detector is implemented with the factchecker. The lie detector analyzes a speaker's voice, body language,heart rate and/or any other information to determine if the person istelling the truth. For example, a video of a speaker is analyzed inconjunction with fact checking the content of the communication toprovide a better assessment of the video. The lie detection analysis isable to be used to provide context to the fact checking analysis or viceversa.

In some embodiments, tracking is implemented. For example, words and/orphrases are tracked as a speech is displayed, throughout the speech orat the end of the speech, the number of repeats is displayed. Forexample, if the President says, “job creation” 5 times in a speech, thattotal is presented to the viewer. The information is also able to usedfor analysis of the speech (e.g. automatically determining the focus ofthe speech). In another example, words and/or phrases are tracked, andsupplemental information is presented related to the trackedinformation. For example, if the President says, we need to “increaseour energy independence,” supplemental information is able to be shownto the viewer that the past 5 presidents have said the same or similaridea, and the viewer is able to understand that this may be a point withlittle substance. The phrases do not have to be verbatim matches;similar matches are able to be found.

In some embodiments, fact check information and/or supplementalinformation is displayed on a mobile device while the user is talking onthe phone. For example, both sides of a user's phone conversation arebeing fact checked, and if something is detected as untrue, the factchecker indicates it to the user.

In some embodiments, user information is acquired to be used by the factchecker and/or supplemental information, for example, for advertising.

In some embodiments, information is presented in real-time, but alsosaved/stored so that the user is able to review the information later.The information is searchable, able to be categorized and/ororganized/formatted in any manner.

In some embodiments, the date/time of a comment is recorded and/ordetermined. For example, if one entity begins a trend by saying a catchyphrase, and then other entities repeat the phrase making it out to betheir original idea, a note is able to be presented giving credit to thefirst entity. Comparisons of dates/times or other implementations areable to be used in determining the first entity versus subsequententities.

In some embodiments, the fact checker is able to detect changed names.For example, high fructose corn syrup is being changed to corn sugar. Bydetecting changed names, either name is able to be used in the factcheck or to provide supplemental information. For example, if a personmakes a comment about “corn sugar,” the fact checker knows to search for“corn sugar” as well as “high fructose corn syrup.” The implementationcould be by using a database which stores name changes and searchesbased on all known names, or by using an embedded search to search forother names, or any other implementation.

In some embodiments, artificial intelligence is used in any aspect ofthe methods and systems described herein. For example, artificialintelligence is used to determine which follow-up question to ask aguest on a television show.

In some embodiments, the fact checker is used with teleprompters and/orto fact check scripts prior to airing. In some embodiments, the factchecker implements measures to prevent hacking, skewing and/or othertampering of the system.

In some embodiments, the fact checker is linked to or is a part of agaming system.

In some embodiments, an independent fact checker device is implementedwhere the device receives information (e.g. a television signal) withoutthe television being on and is able to perform monitoring, searching,analysis, and/or any other tasks.

In some embodiments, one or more of the data structures described hereinare populated automatically, (e.g. by automatically searching andstoring results in the data structure), manually, or a combinationthereof.

In some embodiments, a scam checker is implemented using the factchecker. In some embodiments, the scam checker checks websites and/oremails to determine if they are safe. In some embodiments, the scamchecker determines if an advertisement is a scam (dishonest scheme orfraud). In some embodiments, a scam is detected using a database ofscams. For example, content (e.g. of a website) is compared withlanguage in a database. In some embodiments, a scam is detected bydetermining it is similar to other scams. In some embodiments, a scam isdetected by determining it is mathematically or economically impossible.In some embodiments, a scam is detected by determining the contentincludes misinformation. In some embodiments, a scam is detected bysearching other website and/or weblogs that have commented on the scam.In some embodiments, a user is able to request a website to be factchecked by inputting a URL in a user interface of the fact checker. Anyimplementation is able to be used to detect a scam. In some embodiments,a scam website is indicated as such when displayed in a search engineresult or other webpage (e.g. bubble when mouse over link).

Medical

In some embodiments, a medical fact checker is implemented. The medicalfact checker monitors, processes, fact checks and indicates information.In some embodiments, the fact checker checks the information with alimited set of sources (e.g. validated medical sources). For example, insome embodiments, only medical journals and studies are used as sourcesfor fact checking. In some embodiments, other sources are used, but thesources are still certified as valid before being used. In someembodiments, additional sources are used such as medical websites. Insome embodiments, a designated medical database is used as a source. Forexample, a database of all known illnesses and symptoms is utilized as asource. In some embodiments, users are able to specify their thresholdfor sources to use. The medical fact checker is able to be utilized invarious implementations. In some embodiments, a user inputs (e.g. saysor types), “I think I have X disease, because I have symptoms A, B, andC.” The medical fact checker fact checks the statement by looking up thedisease and symptoms for the disease to see if the symptoms match thedisease. In some embodiments, statistics are determined and indicated tothe user. In some embodiments, additional information about the personis utilized to assist in performing the medical fact check, including,but not limited to, age, weight, height, race, previous conditions, timeof the year, location, genetic conditions, family history, vaccinations,recent activities, recent travels, and any other information. Forexample, if the user says, “I think I have Polio because I have a feverand a headache,” the medical fact checker indicates a 0.0001% chance ofPolio based on recent diagnosis rates and/or any other data. In someembodiments, the medical fact checker indicates possibleillnesses/conditions based on the symptom(s). For example, a list ofpossible illnesses/conditions is presented. In some embodiments,information is displayed to indicate that the listedillnesses/conditions include some symptoms described but not others.

In some embodiments, the medical fact checker prevents misinformationfrom being spread by fact checking email, websites, broadcastinformation and any other information. The fact checker compares theinformation with medical journals and/or other medical information todetermine the validity of the information. For example, an emaildiscussing homeopathic remedies is fact checked and/or to providesupplemental information about the remedies (e.g. what plant the remedycomes from, where it is located, any tests or studies done with theremedy, if the remedy is FDA approved, and other information). Forfurther example, medical analysis is presented regarding the remedy. Insome embodiments, it is determined if the medical information is staleand/or if a newer study has been performed. In some embodiments,information about the source of the information is fact checked and/orsupplemental information presented. For example, the doctor'scredentials are displayed (and fact checked), the medical school'sinformation is displayed, certifications are fact checked and displayed,study information is displayed, any criminal charges, complaints and/orcomments are displayed and/or any other information is displayed. Insome embodiments, a database is implemented to trackdeceptive/false/fake medicine, doctors and/or medical information. Insome embodiments, an email, website and/or other content is analyzed todetermine if an item is being sold. For example, an email is distributedabout being tired, and at the end of the email is an item to curetiredness. The sales pitch is highlighted or indicated in a manner toalert the user of possible misinformation or medical scam.

In some embodiments, the fact checker checks for allergy information ofitems. For example, a device acquires allergy information by scanningthe ingredients label, taking a picture of the ingredients label, usinga barcode reader to determine the ingredients information, using RFIDinformation, and/or any method of determining the ingredients and/orfood preparation information (including, but not limited to, “processedin a plant that also processes X”). The fact checker then compares theinformation to a database of allergy information. In some embodiments,the fact checker uses a higher level approach and fact checks theallergy information by the name of the item. Any other implementation offact checking the item for allergy information is able to be used toassist a user in avoiding allergic reactions, such as postings on awebsite or statements a company has made about a product in a FAQ, blog,or other location. Analysis such as fact checking is able to be done todetermine the reliability of the posting; for example, a bloggerreceives a reliability or credibility rating.

Television/Controversy/Candidates and Other Implementations

FIG. 15 illustrates a flowchart of a method of presenting a viewingschedule according to some embodiments. As described above, apersonalized viewing schedule is able to be implemented using steps offact checking and generating a viewing schedule for a user. In the step1500, information (e.g. a television broadcast) is monitored. In thestep 1502, the information is processed. Processing includes, but is notlimited to converting the information into searchable information,parsing the searchable information into fact checkable portions,separating a show/program into segments based on time, events in theinformation, keywords in the information and/or any other method ofseparating the show/program, storing the segments in a device such as aDVR, ranking the segments, ordering the segments, filtering thesegments, and/or any other processing described herein. In the step1504, a viewing schedule is presented to the user. In some embodiments,the viewing schedule is personalized for the user or the device. Forexample, the viewing schedule is personalized based on personalinformation (e.g., age, sex, and/or other information), user preferences(e.g., music preferences, movie preferences), user input, socialnetworking information (e.g., Facebook® page comments/likes/dislikes),tweets, the user's political classification, popularity ofinformation/trends, and/or any other information. The viewing scheduleis able to include segments of a program, show, movie, commercial,sporting event, or any other content. In some embodiments, one or moresteps are skipped. In some embodiments, more or fewer steps areimplemented. In some embodiments, the order of the steps is modified.

FIG. 16 illustrates an exemplary viewing schedule according to someembodiments. Using the examples directly above and further above, a newsprogram is monitored and processed including determining separatesegments of the show such as a homicide report, a sports report, and aweather report. The segments are displayed to a user in any format, forexample, a view similar to a standard cable channel guide with subsetsof data for each program. The user is able to select which segments towatch instead of selecting an entire show, or as described above, thesegments and their order to watch is automatically generated based onpersonal information of the user or device information. Additionally,the segments do not have to be watched in chronological order. Thesegments are able to be displayed and/or watched based on a user'spreferences or importance. For example, the user wants to watch weatherfirst and then sports even though in the program, sports was first.Additionally, in some embodiments, segments that fall below a user'simportance threshold (as described herein) or other criteria are notdisplayed.

FIG. 17 illustrates a flowchart of a method of performing televisionanalysis according to some embodiments. As described above, televisionanalysis is able to be implemented to improve a user's ability to enjoytelevision programming. In the step 1700, a search string is received.In some embodiments, the step 1700 is skipped. In some embodiments, thesearched for information is automatically determined from personalinformation, previous viewing history, social networking informationand/or from any other information. In some embodiments, additionalinformation is received and/or automatically determined to perform thetelevision analysis, including but not limited to which channel tomonitor for which search string (e.g., different search strings fordifferent channels or the same search strings for different channels),and the time frame of the search. In the step 1702, broadcastinformation is monitored. In the step 1704, the broadcast information isprocessed. Processing is able to include converting, parsing, analyzing,storing, comparing with a search string, auto-comparing, and/or anyother processing. In the step 1706, information is presented based onthe processing. Presenting the information includes but is not limitedto automatically changing the channel, presenting a text/audio/videoalert/alarm, displaying picture-in-picture, playing a video from adetected point, displaying different points in a video where a searchstring is found, and/or any other presentation of information. In someembodiments, one or more steps are skipped. In some embodiments, more orfewer steps are implemented. In some embodiments, the order of the stepsis modified.

FIG. 18 illustrates an exemplary user interface for receiving searchinformation for television analysis according to some embodiments. Asdescribed above, information such as keyword(s)/search string(s),channel(s) to be monitored, start and end time(s) for the monitoring,and/or any other information is able to be entered. The information isable to be entered using any user interface implementation including,but not limited to, text boxes, radio buttons, drop-down menus, voiceinput, movement recognition, SMS message, and/or any other inputdescribed herein.

FIG. 19 illustrates an exemplary screenshot of an alert using televisionanalysis according to some embodiments. An alert is displayed at thebottom of the user's screen when the user's search string (e.g., golf)is found on a different channel. The user is then able to change thechannel to view his desired programming. As described above, otheralerts or effects are able to be used to inform the user that hisdesired programming is being played on a different channel.

FIG. 20 illustrates an exemplary screenshot of search results accordingto some embodiments. By searching recorded information, a user is ableto locate all instances of a search string. As shown, every instancewhere the programming mentions the phrase “Tiger Woods” is displayed.The user is then able to go to each instance using “next” and “previous”buttons or another implementation. This enables a user to quickly viewvery specific desired sections of programming.

FIG. 21 illustrates a flowchart of a method of using opposing argumentsby an opposing entity according to some embodiments. In the step 2100, aspecific fact checking scheme and/or supplemental information scheme isconfigured. For example, a conservative selects a liberal channel to bemonitored, conservative sources to be used, links to be displayed assupplemental information based on keywords detected and/or any otherselections. In the step 2102, a user selects which plan or scheme to usefor fact checking and/or providing supplemental information. Forexample, a user selects a conservative blogger's fact checking scheme.In the step 2104, information is monitored using the selected factchecking scheme. In the step 2106, the information is processed asdescribed herein. In the step 2108, the processed information is factchecked using the selected fact checking scheme as described herein. Insome embodiments, both the selected fact checking scheme and a generalfact checking scheme are used in parallel, and both results are used. Inthe step 2110, a result of the fact checking is indicated as describedherein. In some embodiments, supplemental information is presentedincluding opposing arguments. The opposing arguments are able to beinput and/or generated in the step 2100 or elsewhere. The supplementalinformation is presented with or without fact checking depending on theembodiment. In some embodiments, one or more steps are skipped. Forexample, if a user has already selected a fact checking scheme, steps2100 and 2102 are able to be skipped. In another example, a factchecking scheme is automatically selected based on personal information,political classification, and/or other information about a user (e.g.social networking information), and the step 2102 is able to be skipped.In some embodiments, more or fewer steps are implemented. In someembodiments, the order of the steps is modified.

FIG. 22 illustrates an exemplary user interface for receiving userselections for information analysis according to some embodiments. Forexample, a user is able to select how the information is analyzed orfact checked by selecting ultra-conservative, conservative, moderate,liberal or ultra-liberal. The user is able to select a generalclassification of a fact checking and supplemental information scheme ora specific user's scheme. For example, a cable news network generates afact checking and supplemental information scheme for a competing cablenews network which other users are able to select for when they watchtelevision. Additional information is able to be selected as wellincluding, but not limited to, which channels the scheme is used forand/or any other information. In some embodiments,suggestions/recommendations are presented to users based on previousselections, suggestions by the developer of the scheme, personalinformation, social networking information, and/or any otherinformation.

FIG. 23 illustrates an exemplary user interface for receiving opposingargument selections according to some embodiments. The selections forpresenting opposing arguments and/or other supplemental information areable to include, but are not limited to selecting channels to apply theopposing arguments to, receiving keywords to detect, receiving responsesto keywords, selecting sources to use, and/or selecting a style ofresponse.

In some embodiments, a fact checker fantasy game is implemented. Usersassemble a team similar to a fantasy football team such that each teamis allowed a pre-determined number of players, and a specified number ofplayers at each “position” that can or must be used in each game. A userfor each team then determines each week which players will play thatweek and which are benched. For example, a team roster includes twohosts, a guest, a network and a website. The team could include anyother entities to be fact checked such as a stock picker, weatherperson, politician, candidate, senator, representative, actor/actress,blog, anchor, comedian, announcer, sportscaster,business/corporation/organization, charity, and/or any others. The factchecker then monitors each member of the team for false information,bias and/or any other specified criteria (e.g., hyperbole). For example,host X makes a false statement, so the user's team loses 1 point, sincehost X is on his team. The user with the team at the end of a specifiedperiod of time with the most points is the winner. In a similar butopposite manner, the goal is to pick members of a team who provide falseinformation and/or other specified criteria, and points are awarded tousers when a team member says something false. In some embodiments, auser is awarded a point for each misstatements, bias, and any otherspecified characterization. In some embodiments, a user is awarded apoint for misinformation, and two points for bias (or two points formisinformation and one for bias), and other point amounts for othercharacterizations. In some embodiments, a user is awarded a point foreach characterization and an additional point if the characterization ismajor (e.g., a gross lie or blatant bias) as determined by ajudge/referee, other players or any other implementation. In someembodiments, a user is awarded a point when a team member detectsanother person's inaccuracy (e.g. host X is on the user's team, and hostX points out that guest Y is incorrect, then host X earns a point forthe user's team). Any other parallels of fantasy games are able to beincorporated. In another embodiment, users pick fantasy teams for bias,accuracy, and/or other characterizations. For example, points are earnedfor a team member being biased but points are lost for a team membermisstating a fact. Points are able to be awarded and lost in any desiredmanner. In some embodiments, users are able to configure the manner inwhich points are awarded and lost.

The fact checker fantasy game is able to be implemented in manydifferent implementations. For example, in head-to-head leagues, a teammatches up versus a different team each week or other designated period.The team that earns more points receives a win for that week. A team'stotal points is the sum of all players' points in a starting lineup.Teams with the best win-loss record win or advance to the playoffs. Inanother example, total points leagues are leagues in which teamsaccumulate points on an ongoing basis. The league standings aredetermined by the teams' total points instead of their win-loss record.The teams who accrue the highest total of points throughout the durationof a set time period win or advance to the playoffs. In another example,a “survivor pool” is implemented where each user picks a commentator (orother entity) who will make the first misstatement (or other specifiedcharacterization such as the first biased comment), who will make themost misstatements in a period of time, or who will not make amisstatement for a period of time. The users who are correct, continueto play the next week, and whoever is knocked out of the pool.

FIG. 24 illustrates a flowchart of a method of implementing a factchecker fantasy game according to some embodiments. In the step 2400,user selections are received. For example, a user selects two hosts, aguest, a network, and a website to form his team. Other users makeselections to form their teams. In some embodiments, the users selectmembers of their team from the same pool, and when a member is selected,other users are not able to select that member. In the step 2402, thefact checking fantasy game is processed. For example, processingincludes fact checking team members' comments, awarding points, managingtrades/additions/deletions, determining a winner throughout and/or atthe end of a season, and any other fact checking fantasy game playfeatures. In some embodiments, one or more steps are skipped. In someembodiments, more or fewer steps are implemented. In some embodiments,the order of the steps is modified.

In another embodiment, users earn points for finding and/or providing asource that information presented is wrong or another classification.For example, users watch and highlight/select when information is false,biased, hyperbole or any other classification. The selection is able tobe using a user's remote control, mouse, keyboard, mobile device and/orany other I/O device. Users are able to win prizes or purchase itemsthrough the competitions.

In some embodiments, a single click purchase implementation is provided.In some embodiments, the single click purchase implementation is used inconjunction with any of the advertisement implementations describedherein. For example, an advertisement is displayed on a user'stelevision, and a single click option is presented on a user's mobiledevice or another device. In some embodiments, the single click optionis used in conjunction with fact checking, and in some embodiments, factchecking is not utilized. In some embodiments, the single click optionis not specifically tied to an advertisement but rather other broadcastinformation. For example, a user is watching a football game, and asingle click option to buy a specific player's jersey is presented onthe television or a second device (e.g. mobile phone or computer). Insome embodiments, additional personal information is utilized to selectthe features of the product. For example, a user's height and weight isknown by the system, and an XL jersey is presented. In another example,the user's favorite player is known by the system based on informationon the user's social networking site (e.g. Facebook®). Any other ways ofdetermining a user's information described herein is able to be used toselect and/or personalize the single click advertisement. In someembodiments, the user is able to click on the item, and an advertisementis presented on the user's device(s) for single click purchase oranother type of purchase. For example, a user clicks a football player'sjersey, and an advertisement/screen purchase page is presented for thatjersey. In another example, a user clicks a star's fancy dress at anawards show, and a single click screen purchase page is presented forthat dress or a similar dress.

FIG. 25 illustrates a flowchart of a method of presenting a single clickpurchase implementation according to some embodiments. In the step 2500,information is monitored (e.g., television broadcast information ismonitored as described herein). In the step 2502, the information isprocessed (e.g., broadcast information is converted and parsed forkeywords). Other processing steps are able to be implemented asdescribed herein. In the step 2504, a single click purchaseimplementation is presented based on the broadcast information. Thesingle click purchase implementation enables a user to purchase an itemby a single click of a button or another input. The single clickpurchase implementation is implemented by using stored user information,payment information, purchase information, and/or any other informationthat enables a user to click a button, speak a command, and/or input anyother input to execute a purchase with a single click. For example,after a user clicks the single click purchase implementation, an orderis sent to the selling entity with the customer's purchase information(e.g., name, address, credit card information), and the entity is ableto process the order including billing the user, packaging the purchaseditem, and shipping the purchased item. In some embodiments, the singleclick purchase implementation is presented on the same device that isdisplaying the information (e.g., both on a television). In someembodiments, the single click purchase implementation is presented on adifferent device (e.g., television information displayed on television,and single click purchase implementation displayed on mobile device). Insome embodiments, the single click purchase implementation isaccompanied by fact checking information and/or supplementalinformation. For example, the single click purchase implementation isincluded with an advertisement, and the advertisement is fact checked toinform the user if the advertisement is truthful. In another example,supplemental information such as prices of competing products aredisplayed. In another example, reviews and/or ratings of: the product,the company selling the product, the network selling the product and/orany other reviews or ratings are displayed with the single clickpurchase implementation. For example, complaints and/or positive remarksabout a shopping network are displayed along with the single clickpurchase implementation. The single click purchase implementation isable to be implemented as button on a touch screen, a hard button on amobile device or remote controller, or through any other inputimplementation described herein. In some embodiments, a competingadvertisement is displayed with the advertisement, and each has a singleclick purchase implementation. In some embodiments, the single clickpurchase implementation incorporates bidding by competing advertisementssuch that the advertisers are able to lower the price of the product,and the user is able to purchase the item at a desired price. In someembodiments, the single click purchase implementation is used forpurchasing an auctioned item. For example, a user watches an auction ontelevision, and presses a single button to make a higher bid. In someembodiments, the supplemental information accompanying the single clickpurchase implementation suggests a movie or television programming tosubscribe to, download, stream, rent and/or purchase. The supplementalinformation is able to be based on monitoring television programming,movies watched, social networking information (e.g. Facebook® pageinformation and recent tweets), personal information, and/or any otherinformation. In some embodiments, foods are suggested for purchase basedon programming (either directly related or indirectly related). Forexample, a user watches a cooking program, and the recipe is displayed(e.g. on the mobile device) for the user including items to be deliveredto the home or picked up. The user is then able to purchase the itemswith a single click. In an example of an indirectly related foodsuggestion, the monitoring determines that a user is a football fan, andthat the championship is upcoming. A suggestion of a delivery of pizzafor that day is presented to the user for purchase with a single click.In some embodiments, the implementations described related to singleclick purchasing are able to be implemented using multiple clicks.Although the word “click” is used as an example herein, any single inputis able to be used such as a single voice command. In some embodiments,the single click purchase implementation is used for making donationsand/or contributions (e.g., an advertisement is for an animal shelter,and a single click purchase implementation allows a user to make adonation to the shelter). In some embodiments, the advertisement is anational advertisement, but the single click purchase implementationenables a user to donate to a local chapter of the organization which isdetermined based on the user's location. In some embodiments, one ormore steps are skipped. In some embodiments, more or fewer steps areimplemented. In some embodiments, the order of the steps is modified.

FIG. 26 illustrates an exemplary single click purchase implementation onmultiple devices according to some embodiments. As described above, thesingle click purchase implementation is able to be implemented onmultiple devices such as a television 2600 and a mobile device 2602(e.g., smart phone or tablet). For example, the television 2600 displayshome shopping programming, and a user's mobile device is able tocoordinate with the television programming to offer a single clickpurchase button 2604 where the user taps the smart phone screen, and anorder is placed. In some embodiments, supplemental information 2606 suchas fact checking information, an additional advertisement, comparativeshopping information and/or any other information described herein isdisplayed with the single click purchase button 2604 on the mobiledevice 2602. In some embodiments, the single click implementation isimplemented on the same device as the programming. For example, homeshopping programming is presented on a television, and a single clickpurchase implementation is presented on the television. In anotherexample, the single click purchase implementation is overlaid on astandard television advertisement.

In some embodiments, a candidate fact checker is implemented. Thecandidate fact checker tracks and stores candidate informationincluding, but not limited to, flip-flops, main arguments/points,positions on issues, dates of positions, advertisements by the candidateor associated people/groups, contact information, strengths/weaknesses,how to contribute to the campaign, who has contributed to the campaignor related groups (e.g., PACs/SuperPACs), associated PACs/SuperPACs,direct quotes by the candidate and/or associates, video clips of thecandidate, audio clips of the candidate, and/or images of the candidate.The information is able to be stored and sorted in any manner; forexample, the candidate's positions on issues are ranked from strong toweak, so that the user knows that a candidate is strongly in favor of X,but only mild cares about Z. Additionally, voice, text, photo and/or anyother recognition is able to be used to detect and post information.Candidate quotes are able to be used to ensure the media does not takequotes out of context. For example, if a quote is detected out ofcontext, the candidate fact checker presents the full quote and/or aclip of the quote. The candidate fact checker information is able to bepresented when an advertisement is displayed for or against a candidate,when a candidate is making a speech on television, when a candidate isappearing in an interview, when a spokesperson or other associate isspeaking or being interviewed, and/or any other event related to thecandidate. The candidate information is able to be stored in any type ofdata structure. In some embodiments, the candidate fact checkerinformation is displayed on a second device (e.g., mobile device) whenthe candidate or related event is detected. For example, a candidateappears on a talk show and provides his views. After the candidate isdetected (e.g. by face recognition), statistics regarding the candidateare displayed in text at the bottom of a user's television or on theuser's mobile device. In some embodiments, the statistics displayed arebased on the detected candidate as well as the detection of keywords inthe discussion. For example, Candidate A is detected, and it is detected(e.g., by monitoring, converting, parsing, and/or comparing the wordsspoken with a database of keywords) that the interview is about theenvironment; the Candidate's Congressional voting record related toenvironmental topics, and/or campaign contributions by energy companiesis displayed.

FIG. 27 illustrates a flowchart of a method of implementing a candidatefact checker according to some embodiments. In some embodiments, thecandidate is a political candidate. In the step 2700, candidateinformation is detected (e.g., while monitoring broadcast information).Detecting the candidate information includes detecting a candidate byfacial recognition, voice recognition, image recognition, namerecognition, and/or any other recognition. In some embodiments,detecting the candidate includes detecting people associated with thecandidate (e.g., a spokesperson or campaign manager). For example, adatabase stores the candidate and the people associated with acandidate, so that when the associated person is detected, he/she isrecognized as being linked to the candidate. In some embodiments,detecting the candidate information includes detecting a comment byand/or about the candidate (e.g., candidate's name), an advertisement byand/or about the candidate and/or against the candidate's opponent,and/or any other information from or related to the candidate. Thecandidate information is able to be comments made by the candidate orassociates of the candidate, advertisements, and/or any otherinformation from or related to the candidate. In the step 2702,candidate information is processed. Processing is able to includeconverting, parsing, storing, classifying and/or any other processingdescribed herein. For example, a candidate's comment is classified as aflip-flop and stored in a database under “flip-flops.” In anotherexample, advertisements are classified as attack advertisements,positive advertisements, and/or another classification. In someembodiments, advertisements are rated on a scale of very positive tovery negative (e.g. 10 is very positive and 1 is very negative). In someembodiments, advertisements are fact checked (either automatically ormanually) and stored with an accuracy rating which is then able to bedisplayed automatically with the advertisement when the advertisement isdisplayed. In the step 2704, the processed candidate information isanalyzed. Analyzing is able to be any analysis including, but notlimited to, fact checking or searching for supplemental information asdescribed herein. In the step 2706, supplemental candidate informationis presented based on the candidate and/or the candidate information. Insome embodiments, the supplemental candidate information includes acampaign contribution implementation. For example, in conjunction withan advertisement for a candidate, a campaign contribution implementationis displayed on a user's mobile device enabling the user to easily makea campaign contribution. In some embodiments, the campaign contributionimplementation is a single click campaign contribution implementationsimilar to the single click purchase implementation described herein.The campaign contribution implementation is able to be implemented onthe same device presenting the candidate information or on anotherdevice. For example, a user is watching a political advertisement on histelevision, and a single click campaign contribution implementation isdisplayed on his smart phone. In some embodiments, the single clickcampaign contribution implementation utilizes additional informationabout the user including, but not limited to, previously submittedinformation, personal information (e.g., credit card information), auser's political classification, device information, social networkinginformation, previous donation/contribution information, informationrelated to the advertisement, information against the advertisement(e.g., the user is disgusted by a political attack advertisement andchooses to contribute to the candidate being attacked in theadvertisement), and/or any other information. In some embodiments, thecandidate fact checker is implemented for state propositions, politicalaction committees, and/or other political entities. In some embodiments,a user's information (e.g., political classification) is used todetermine the supplemental information displayed. For example, it isknown that the user is concerned with the environment, but not taxes.Thus, the supplemental information displayed for the user is directedtowards environmental issues (e.g., the candidate voted several times onenvironmentally-friendly bills). In some embodiments, one or more stepsare skipped. For example, the steps 2702 and 2704 are able to be skippedin an implementation that detects a candidate and then automaticallydisplays supplemental information about the candidate (e.g., thecandidate's 3 biggest flip-flops). In some embodiments, more or fewersteps are implemented. In some embodiments, the order of the steps ismodified. The steps of the candidate fact checker are able to beperformed automatically, manually and/or semi-automatically.

In some embodiments, a controversy tracker is implemented. Thecontroversy tracker is able to automatically, manually, or in acombination of automatically/manually determine a controversy.Automatically determining a controversy is able to be implemented bymonitoring for a words such as “controversial” or “controversy” and anyassociated story, comment, or other information, or anotherimplementation. Manually determining a controversy is able to be by ahuman indicating a story is a controversy. A combination ofautomatically and manually determining a controversy includesautomatically monitoring stories and indicating possible controversiesand having a human filter the possible controversies and indicating thedetermined controversies. Once the controversy is determined, thecontroversy is associated with a person, company, organization, or anyother entity. For example, a database (or other data structure) storesentity information in one column or row and controversy information inanother column or row. The controversy information is then indicated ordisplayed when that entity is viewed, heard or otherwise recognized(e.g., by face, voice or name recognition). In some embodiments, thecontroversy information is stored with the entity information describedherein.

For example, Commentator Z makes a controversial statement on his radioshow. The statement is detected as controversial and stored accordingly.When Commentator Z appears on a television show 5 months later, thecontroversial statement and/or a summary of the controversy is displayedwith the Commentator Z using any method described herein. In anotherexample, when a food processing plant has violated regulations, thecontroversy is indicated to users so that they are able to avoid thecompany's products. Other violations of the law are tracked, recordedand indicated, such as oil spills, other environmental misdeeds (e.g.pollution), avoidance of taxes (e.g. Company Y paid $0 in taxes lastyear), and/or any other controversies. In some embodiments, a user isable to use his device to determine if an entity has a controversyattached to it. For example, a user points his smart phone camera atBrand X, and the phone recognizes the brand, compares the brand withsource information (e.g., a controversy database), and indicates Brand Xhas had an e. coli outbreak at one plant. In some embodiments, when acontroversy is determined for a brand, a competitor is recommended. Insome embodiments, only competitors without a controversy are displayed,or a competitor with the fewest controversies is displayed.

FIG. 28 illustrates a flowchart of a method of implementing acontroversy tracker according to some embodiments. In the step 2800,information is monitored. In the step 2802, a controversy is detected.In the step 2804, the controversy is processed (e.g. a controversy isstored in a database where the database associates the controversy withan entity). For example, a person makes a controversial statement, thenthe statement and the person's name are stored in related columns orrows of database. In the step 2806, the entity is recognized at a laterdate (e.g., facial or voice recognition, by name and/or any otherrecognition). In the step 2808, the previously stored controversy isdisplayed in any manner described herein. In some embodiments, one ormore steps are skipped. In some embodiments, more or fewer steps areimplemented. In some embodiments, the order of the steps is modified.

In some embodiments, the fact checker and/or other implementationsdescribed herein are able to be used with Google glasses or a similartechnology (e.g., helmets, headphones, baseball caps, glasses,sunglasses, contact lenses, goggles with a heads up display). In someembodiments, the fact checker is incorporated in car, motorcycle,airplane systems, boat/cruise ship and/or other transportation systems.In some embodiments, the fact checker fact checks a user's life and whatthe user senses (e.g., sees, hears). The implementation is similar towhat has been described herein (information is monitored, processed,fact checked and then a result is indicated). For example, a user'sglasses are able to receive audio and video signals and process thosesignals including converting the signals to text and comparing portionsof the text with source information (e.g. online sources). Then, aresult is displayed on the glasses to indicate whether the detectedinformation was true, false or any other characterization. In someembodiments, the glasses provide supplemental information, provideentity validity ratings, and/or any other implementation describedherein.

In some embodiments, fact checking and/or supplemental information ispresented in conjunction with a movie at a movie theater. For example,the movie is monitored, processed, fact checked and/or searched, andfact checking results and/or supplemental information is presented on auser's mobile device and/or sent to another device (e.g., a homecomputer). For example, when an advertisement is placed (possiblysubtly) in the movie or when specific content is detected, a relatedadvertisement is also displayed on the user's mobile device. In someembodiments, the advertisement includes a single click purchaseimplementation. In some embodiments, the advertisement is arecommendation to purchase a ticket for one or more movies based on themovie currently being watched, previously watched movies, personal orsocial networking information, and/or any other information. Forexample, the user is watching a comic book movie, and a purchase ticketadvertisement for an upcoming comic book movie is presented to the useron his mobile device (possibly single click). In another example, musicfrom the movie is presented on the user's mobile device for purchaseand/or download. In some embodiments, the fact checking and/or thesupplemental information is displayed discretely during the movie. Forexample, an advertisement is displayed at a lower lighting setting toavoid disturbing other moviegoers. In some embodiments, the factchecking and/or supplemental information is stored (e.g., queued) untilit is displayed at an appropriate time (e.g., when the movie is over).For example, an advertisement is stored in the device until the creditsare detected, and then the advertisement is displayed. In anotherexample, when the device detects light above a threshold, the deviceknows that the movie is over or the user is outside of the theater, sothe advertisement is able to be displayed. In another example, thedevice uses GPS to determine the user's location, and when the user isoutside of the theater, the supplemental information is displayed. Insome embodiments, the supplemental information is able to provide acountdown of when the next interesting, exciting, memorable, and/oranother highlight of a movie will occur or when a specified characterwill appear next. For example, based on user reviews, social networkinginformation, and/or any other information, the device gathers specificpoints of a movie that are or might be of interest to a user, andprovides a countdown or a “heads up” alert based on the current time ofthe movie. In some embodiments, supplemental information asks for a userto input a review of the movie. In some embodiments, the review is asingle click implementation (e.g., the user is presented 1-10 asselectable options, and the user selects one option). In someembodiments, similar implementations are provided for televisions orother devices (e.g., at home, at a sports bar).

In some embodiments, a device (e.g., television, mobile device, camera,video camera, webcam, game console) monitors users. For example, thedevice detects by listening to (e.g., by microphone) and/or seeing areaction (e.g., by camera) by the user to a commercial, advertisement,movie, show and/or any other programming or event. Possible responsesthat are monitored and detected include, but are not limited to, alaugh, crying, an expletive, a positive comment, a negative comment, asmile, a frown, a surprised face, a furrowed brow, a hand gesture,clapping, walking away, walking toward, a channel change, a textmessage, a tweet, or a Facebook® post about the programming, and/or anyother response. The reaction is then able to be used to perform dataanalysis and/or present future programming. For example, if a userreacts negatively to a certain type of commercial (e.g., comedy) or aspecific commercial, that type of commercial is not presented to theuser again or that specific commercial is not presented again. Themonitored and collected data is stored in a data structure (e.g.,database). For example, a commercial is displayed, and a user laughs.The laugh or a computer code representative of a laugh is stored in adatabase to correspond with the commercial and that user or device.Then, the same commercial is displayed, and the user laughs again.Again, the response is stored. The same commercial is displayed again,but this time the user does not laugh. The new response is stored inaddition to or instead of the previous responses. Based on the newresponse, the commercial is not displayed to the user again. Theresponses are able to be retained for a user and/or device and based onthe gathered data further analysis and actions are able to be taken. Forexample, if a user does not laugh at three comedic advertisements, thencomedy advertisements are no longer presented for that user. In anotherexample, if a user laughs the first four times but changes the channelor station when hearing several different comedic advertisements each afifth time, the system is able to determine that the user's thresholdfor a comedic advertisement is four and does not attempt to present thesame comedic advertisement a fifth time for future advertisements. Inanother example, responses are monitored for political advertisements,and if is detected that the user is frustrated with mudslingingadvertisements, future advertisements presented are positiveadvertisements.

FIG. 29 illustrates a flowchart of a method of performing analysis of auser according to some embodiments. In the step 2900, a device monitorsa user. In the step 2902, the device processes the monitoredinformation. For example, a smile is detected and a representation of asmile is stored in a database with the corresponding monitoredinformation and the user or the device. For example, a smile is a 0, afrown is a 1, crying is a 2, and so on. In the step 2904, an action istaken based on the processing. For example, the advertisement is madeavailable for display to the user again, or the advertisement is removedfrom the playing queue. In some embodiments, one or more steps areskipped. In some embodiments, more or fewer steps are implemented. Insome embodiments, the order of the steps is modified.

In some embodiments, fact check information is utilized in determiningsearch engine results. For example, in addition to standard searchengine processing, the results of the search engine are fact checked asdescribed herein, and results that contain many factually incorrectitems are placed lower on the search result list. For example, astandard search returns Items 1-10, and then the items are fact checked,and Item 1 is highly inaccurate in terms of factual accuracy. Item 1 isplaced lower on the list based on the inaccuracies. In another example,10 items are found and are deemed highly relevant to the search;however, Item 1 has no factual inaccuracies, and is placed at the top ofthe list. The affect of the fact check on the displayed results dependson the implementation. For example, in some embodiments, the fact checkonly changes a position of a search result if the search result has asignificant number (e.g. 10 or above a threshold) of factualinaccuracies. In some embodiments, the fact check has an equal weight tothe search, so if a search result is highly relevant but has severalfactual inaccuracies, the search result is positioned below a lessrelevant result with fewer factual inaccuracies. In some embodiments,search results are grouped by relevance (e.g., search results that have100% relevance, search results that have 95-99% relevance, 90-94%relevance, and so on), and the fact check affects the search resultswithin the group but does not cause the search results to fall to alower relevancy group. The weighting of the search relevance and factcheck is able to be any implementation (e.g., 99%/1%, 90%/10%, 80%/20%,50%/50%, 20%/80% or any other scheme). In some embodiments, bias of asearch result is determined and affects the position of the searchresult in the list (e.g., a highly biased page is lower in the list thana neutral page).

FIG. 30 illustrates a flowchart of a method of utilizing fact checkingto determine search engine results according to some embodiments. In thestep 3000, a search is performed. The search is performed in any manner(e.g., a user inputs a search string, the search string is located insources such as web pages and/or documents using any search technology,and search results are returned). In the step 3002, a fact check of thesearch results is performed. In the step 3004, a result of the combinedsearch and fact check is displayed. For example, a list of web pages isdisplayed with the top web page being the most closely related to thesearch string and also a factually accurate page. Therefore, when a usersearches for a political topic and several web pages discuss the topicbut completely distort the truth, those web pages are displayed lower inthe list even though they are relevant to the search string. In someembodiments, the steps of fact checking and searching are pipelined oroccur in parallel. In some embodiments, one or more steps are skipped.In some embodiments, more or fewer steps are implemented. In someembodiments, the order of the steps is modified.

In some embodiments, subjective fact checking is implemented usingsocial networking information. For example, a user asks if the new “XYZMovie” is worth seeing. The subjective fact checker monitors, searches,detects, compares, calculates and/or indicates a result based socialnetwork information (e.g. Twitter posts, friends' Facebook® pagecomments). Furthering the example, the subjective fact checker searchesfor the movie title and accompanying text in a person's friends'Facebook® page comments and determines three friends said the movie was“awesome.” The word “awesome” with a “3” next to it is returned, or theword “awesome” is assigned a number in a data structure and retrievedand indicated, or another implementation is used. In some embodiments,the social networking information is used in conjunction with othersubjective sources (e.g., critics' reviews) and/or objective sources. Inanother example, friends' usernames are located on review websites andcorresponding reviews are obtained and utilized. In some embodiments,social networking information includes social media information.

In some embodiments, historically parallel supplemental information isprovided with broadcast information and/or other information. Forexample, if a commentator argues that the EPA is unnecessary, anexplanation of why the EPA was started is indicated. In someembodiments, examples are provided (e.g. acid rain was a problem and nowthrough the efforts of the EPA, acid rain is less of a problem). In someembodiments, citations are included. The historically parallelsupplemental information is able to be searched for and/or located in adata structure (e.g. a database). For example, a database includescurrent topics and corresponding historical supplemental information.Examples of parallels include: getting rid of unions: terrible workingconditions; shutting down the EPA: excessive pollution; and the burst ofthe housing bubble: the Great Depression.

In some embodiments, an automatic comment or rebuttal by acelebrity/commentator/organization, or any other entity is presented.For example, any time News Org X is mentioned by a competitor,statistics that show News Org X dominates the ratings compared to thecompetitor are presented. More specifically, when a user watches NewsOrg A on channel 213, and a commentator on News Org A states that NewsOrg X is misleading the public, a popup, caption, and/or any otherindicator described herein displays a chart of News Org X's and News OrgA's ratings.

In some embodiments, sources for each comment on a television broadcastare provided. The sourcing is able to be implemented by monitoringbroadcast information, processing the broadcast information, searchingfor a source of the broadcast information and indicating a result. Whenstatements are unsourced, unverified, or uncorroborated, the comment isindicated as unsourced, unverified or uncorroborated. For example, anews agency reports that: “Person X was unarmed.” However, no source ismentioned by the news agency. To inform the user that the information isunsourced, the text is indicated as unsourced, for example, bycolor-coding or labeling the text as “unsourced” or similar language, oranother indicator.

In some embodiments, when a commentator appears (e.g., on a televisionshow), the commentator's web site (or Facebook® page) or a link to thecommentator's web site or page is presented. In some embodiments, thelink is presented on a second device (e.g., mobile device). The link isable to be a link to specific content on the site. For example, thecommentator is talking about a specific article, which he also haswritten about online. By following the link, a viewer is able to receivemore information than available on the television program. In anotherexample, the link is to a website for purchasing the commentator's book.In some embodiments, the link is to rebuttal content provided by thecommentator.

In some embodiments, an automatic, manual, or semi-automaticpresentation of content is implemented to prove or disprove apoint/argument. For example, video clips showing the previous commentsby the commentator are shown to provide a full context of the currentcomment.

In some embodiments, the importance rating includes classifyinginformation such as an article or story as: critical, important,helpful, nonsense, waste of time, trivial, distraction, irrelevant,and/or any other classification. For example, during a politicalcampaign, many stories are presented regarding the candidates. A storyabout a candidate's cat 20 years ago could be classified as“distraction” or “irrelevant,” whereas a story about a candidate'seconomic policy is classified as “important.” The classification is ableto use text descriptions, numerical classifications (e.g., 10 iscritical and 1 is irrelevant), color coding (e.g., edge of the screen ishighlighted a certain color indicating importance), and/or any otherclassification. In some embodiments, information is not shown if it isclassified in a certain manner and/or is below a threshold. Theclassification is able to be performed automatically, manually, orsemi-automatically. The classification is able to be stored in a datastructure. Age of a story is able to be a factor in classifyinginformation. For example, a story that is 30 years old is likely to bedeemed less relevant than something that happened less than a year ago.Classifying factors include, but are not limited to, age of theinformation, content of the information (e.g., relevance to the country,relevance to individuals, and other relevance), quality of the content,and/or any other factors. Once a story is classified, that story and/orany repeat stories involving the content have the importance ratingindicated.

In some embodiments, similar to counter-arguments described herein,supplemental arguments are indicated. For example, when an argument isdetected, instead of providing a counter-argument to the argument, asupplemental argument is provided. For example, a commentator statesthat President Z should be re-elected because of A, B and C. When thefact checker detects that a topic of President Z and re-election isdiscussed in a positive manner, supplemental arguments in support ofthat argument are presented on a user's device or secondary device. Thedetermination of whether the argument is for or against a topic is ableto be determined from the comment itself, based on the person or entitymaking the comment, based on the source of the forum (e.g., whichbroadcast network, website) and/or a combination thereof. In someembodiments, both counter-arguments and supplemental arguments areindicated.

In some embodiments, the fact checking system has its own Twitteraccount (or other microblogging social networking service) or has accessto a twitter account so that the results of the fact checking areautomatically posted on the twitter account. For example, the factchecking system monitors communications (e.g., broadcast, web, Twitter,mobile, and/or any others), processes the communications, fact checksthe communications, and when misinformation or another characterizationis detected/determined, a tweet is sent. The tweet is able to includeany identifying information (e.g., Senator A said, “the President wasted$100M on this trip,” but the truth is the cost is under $1M). In someembodiments, the fact checking system has separate accounts fordifferent items (e.g., 1 for broadcast information, 1 for webinformation, and so on). In some embodiments, the fact checking systemhas separate accounts where each account uses different sources for factchecking. In some embodiments, the fact checking system providessupplemental information, and/or any other information on the twitteraccount.

In some embodiments, the fact checking system has its own Facebook®account (or other social networking account or blog) so that the resultsof the fact checking are automatically posted. The fact checking systemwith Facebook® account functions in a similar manner to the Twitteraccount by monitoring, processing, fact checking, and posting to theaccount.

In some embodiments, fact checking is performed in the cloud, andresults are indicated on a user device. For example, monitoredinformation is sent from a device (e.g., television or smart phone) tocloud computing device(s) which then perform fact checking (orsupplemental information searching, and/or other analysis describedherein) by comparing the information with source information. Then, thecloud computing device(s) send result(s) of the fact checking to a userdevice (e.g., the same device that monitored the information and/oranother device). For example, a user's smart phone monitors broadcastinformation, sends the information to the cloud which fact checks theinformation and sends a result of true or false to the user's televisionwhich displays the result. In some embodiments, processing of theinformation occurs on the monitoring device (e.g., information isparsed, and the parsed segments are sent separately to the cloud), andin some embodiments, the entire information is sent to the cloud whichprocesses the information. In some embodiments, the processing on theuser's device includes converting the monitored information into text ora similar data type to minimize the amount of data sent to the cloud.

In some embodiments, identification information of the monitoredinformation is sent to and from the cloud instead of the monitoredinformation to minimize the amount of data sent to and from the cloud.The identification information is able to include any type ofidentification information including, but not limited to, contentidentification (e.g., name, filename, channel/station), numericalrepresentation of content segment identification, a timestamp, anidentifier for matching with the corresponding monitored information,user information, device information, and/or any other identifier. Forexample, the code identifies which broadcast network and the start andend times of the segment to be fact checked. In another example, thecloud monitors communications/information (e.g., broadcast, web, mobile,others), and each communication or communication segment has anidentification code. The communication monitored and/or displayed by auser device has a matching code. The user device is able to send thecode to the cloud which matches the code with the appropriatecommunication, and then performs a task (e.g., processes and fact checksthe communication and/or searches for supplemental information). Thecloud is then able to send the identification information and a resultto the user device which is then able to display the result with thecorresponding communication. The identification information isimplemented such that the cloud computing fact checking still providesreal-time fact checking results displayed on a user's device inreal-time. The cloud is able to be implemented to fact check allinformation or a subset less than all information. Examples of subsetsless than all information include, but are not limited to, all broadcastinformation is fact checked, only the top 10 most popular Internetwebsites are fact checked, and/or broadcast information from one networkis fact checked. In some embodiments, the cloud fact checks onlyinformation specified by a user to monitor. In some embodiments, thecloud is synchronized with the user's device (e.g., television and/orsmart phone), and the cloud monitors, processes and/or fact checks whatis being viewed/listened to by the user. In some embodiments, the cloudutilizes multiple fact checking implementations to fact check manycommunications simultaneously. In some embodiments, the cloud avoidsredundancy by determining that a fact check of Program Z is alreadybeing performed for User A, and User B is watching the same program, thefact check is not performed a second time, rather the results from thefirst fact check are provided to User B.

As an example of a cloud computing fact checking system, a user device(e.g., a smart phone) displays a news program. An identification code issent to the cloud. The identification code includes a device ID and acontent ID identifying the news program. The cloud computing factchecking system monitors, processes, and fact checks the news program.The results information is sent from the cloud to the user device, andthe results information is displayed on the user device in real-time.

As another example of a cloud computing fact checking system, a userdevice (e.g., a television) displays a news program. The user devicemonitors and processes (e.g., converts and parses) the news program intofact checkable portions. An identification code of each fact checkableportion is sent to the cloud. The identification code includes a deviceID and a fact checkable portion ID identifying the portion of the newsprogram content to fact check. The cloud computing fact checking systemfact checks each fact checkable portion. The results information is sentfrom the cloud to the user device for each searchable portion, and theresults information is displayed on the user device in real-time. Ifadditional users are watching the same news program and receive factchecking information, the same results are able to be sent to thosedevices without performing the fact check again by sending the sameresult information with a different device ID for each user device.

FIG. 31 illustrates a flowchart of a method of utilizing cloud computingfor fact checking and providing supplemental information according tosome embodiments. In the step 3100, information is monitored (by a userdevice, the cloud, and/or another device). In the step 3102, themonitored information or identification information is sent to cloudcomputing devices. In some embodiments, the information is processed inthe cloud, or the information is processed and then sent to the cloud.In the step 3104, fact checking and/or supplemental informationsearching as described herein is performed in the cloud. In the step3106, a result of the fact checking and/or supplemental informationsearching is sent from the cloud to a device or a group of devices wherethe result is indicated (e.g. a user's mobile device or television,millions of televisions). In some embodiments, more or fewer steps areimplemented, and/or the steps are modified. In some embodiments, thestep of monitoring is not included, and/or other information is sent tothe cloud. In some embodiments, the result is retrieved (e.g., pulled)from the cloud by a device, and in some embodiments, the result ispushed from the cloud to a device.

In some embodiments, the fact checking glasses, goggles, hat, clothing,and/or other items described herein are able to be used while readingnewspapers and/or other printed material, and the device provides theuser with fact checking and/or supplemental information on the lenses ora display in/near the lenses. In some embodiments, the glasses or otherdevices are able to be used to fact check or supplement a billboard,business names, food labels, allergen information, and/or digitalinformation (e.g., information on a computer monitor or display). Insome embodiments, the glasses or other devices are able to be used forprice comparison. In some embodiments, the device projects the factcheck and/or supplemental information onto the printed material (e.g.,using a projection device embedded in the device). In some embodiments,a user's mobile device (e.g., smart phone or tablet) is able to beplaced on a print material, scans the print material with a camera onone side and displays the print material on the mobile device screen onthe opposite side along with any fact checking and/or supplementalinformation generated by analysis of the print material.

FIG. 32 illustrates a diagram of fact checking glasses according to someembodiments. The glasses 3200 include a frame 3202, lenses 3204, and acamera 3206. In some embodiments, the lenses 3204 include a display 3208or the display 3208 is able to be flipped down or configured in anymanner to be coupled to the frame 3202. The camera 3206 is able toacquire visual data by scanning and/or taking a picture of objects suchas a newspaper. In some embodiments, the camera 3206 is capable ofprocessing the data including converting the data to text, parsing thedata, fact checking the data and/or providing supplemental information,and indicating a result of the fact checking/supplemental data search onthe display 3208 or another location. In some embodiments, the camera3206 acquires the data, and some or all of the processing, factchecking, searching and/or indicating occurs on another device (e.g., inthe cloud). For example, the camera 3206 acquires newspaper data, sendsthe data or identifying information to the cloud for converting,parsing, fact checking, and then the cloud sends the results to thecamera 3208 (or directly to the display 3208) for display on the display3208 or elsewhere. In another example, a processor is also included withthe glasses and is coupled to the camera 3206 and display 3208, and theprocessor processes and fact checks the information and sends the resultto the display 3208.

In some embodiments, a fact checking GUI utilizes overlays, underlays,pop-ups, pop-unders, menus, frames, and/or any other component. Forexample, fact checking information (e.g., a result) is overlaid on ascreen. Pop-ups are able to provide cites, opposing arguments, rebuttalinformation, advertisements, and/or any other information. A backgroundof the GUI is able to be changed as fact checking occurs (e.g.,background changes from green to red as more inaccuracies aredetermined). The background is able to be an overall background, or aspecific background (e.g., a commentator's background, a host'sbackground). In some embodiments, distortions are used to indicate factchecking results. For example, an image or icon of an entity isdistorted as the fact checking system determines the truth is beingdistorted. For example, a commentator's image is a natural imageinitially, but as the host provides misinformation, the image becomesmore and more distorted. In some embodiments, if the host corrects themisinformation, the host's image is restored incrementally. Anydistortion is able to be implemented (e.g., blur, warping, darkening).In some embodiments, 3D is implemented such that fact checking resultsand/or supplemental information is generated to appear to come at theuser. For example, only fact checking results and/or supplementalinformation is presented to appear to come at the user while thebroadcast information is a standard display. In some embodiments,inaccurate, misleading, biased and/or other characterized information isdisplayed to appear to come at the user. In some embodiments, correctiveinformation is displayed to appear to come at the user. In someembodiments, accurate information is displayed to appear to come at theuser, while the inaccurate information does not, or vice versa. In someembodiments, a result of a fact check appears to come at the user, whilethe fact checked information is highlighted on the screen. For example,a commentator makes a misleading comment, which is displayed at thebottom of the screen, and the result “misleading” is displayed to appearto come at the user. In some embodiments, the fact checking informationand/or supplemental information is presented using different icons (e.g.on a user's fact checking glasses). In some embodiments, lights and/orsounds on a television, in a house, and/or on a phone, change based onthe truth/misinformation, bias, and/or other characterizations. Forexample, lights on the side or back of a television or in the housechange to blue when a liberal bias is detected, red when a conservativebias is detected, and green when an environmental message is detected.In another example, the lights flash red when misinformation isdetected, and the brightness of the red depends on how significant themisinformation is. The color and other effects of the lights are able tobe controlled using any processor or controller configured accordingly.For example, a computing device sends a signal to a light controller toaffect the changes in the lights. In some embodiments, a popup or a webpage accompanying a website is used to display the fact checking and/orsupplemental information for a website. For example, a user goes toWebsite X, and a pop-up from a browser plug-in shows the factuallyinaccurate and/or supplemental information of Website X. In anotherexample, a browser page, frame, and/or background has a color or changescolor based on the factual accuracy and/or bias of a page. In anotherexample, each factually inaccurate, biased and/or other characterizedinformation is highlighted on the web page. In some embodiments, thehighlighting is performed by overlaying highlighting on the web pagewithout actually changing the web page. For example, a hidden frame oranother implementation is used to display the highlighting and/oradditional information (e.g., supplemental information). In someembodiments, the information is selectable (e.g., a web page link) tosee the evidence of the bias and/or misinformation. In some embodiments,fact checking information and/or supplemental information is an overlayprojected by a mobile device or other device on a television or anotherscreen. In some embodiments, the fact checking information and/orsupplemental information is projected by a television or other deviceonto a television frame, wall and/or another object. In someembodiments, a user's seating area is affected in conjunction with thefact checking. For example, a user's chair vibrates when misinformationis presented, a user's chair tilts one way or the other when bias isdetected (e.g., left for liberal and right for conservative), a sofarocks when a lie is detected, and/or any other effect. The effects areable to be implemented in any manner. For example, a signal is sent froma television to a device configured to receive and respond to the signal(e.g., a motorized chair).

In some embodiments, users are able to input keywords, topics, and/orother information, to track for bias. The bias detector tracks how oftena keyword is detected, determines if the keyword is used positively ornegatively, and/or any other analysis to determine bias. For example, adevice is configured for receiving a user-specified input for biasdetection, automatically monitoring for the user-specified input, andautomatically indicating bias based on detection of the user-specifiedinput. User-input information is able to be stored in a data structurefor continued use. The implementation is able to be performed inreal-time. In some embodiments, the implementation is performedautomatically, manually, and/or the results are displayed automatically.

In some embodiments, determining bias is performed by classifyingstories as liberal, moderate or conservative. In some embodiments,sections of stories are classified. In some embodiments, stories areclassified as ignored or underreported, or over reported. Then, based onthe classifications, the reporting amount and/or any other information,bias is determined. For example, stories are monitored, classified, andbias is computed and indicated.

In some embodiments, the fact checking system validates itself or isable to be validated by others. For example, if enough (e.g., above athreshold) users flag a fact checked result, then the fact checkingsystem indicates that the fact checked result is under review. In someembodiments, users are able to flag a real-time fact checked resultusing voice commands. For example, a user is watching television, and afact check result displays “X's comment is false,” within a designatedtime frame (e.g., 2 seconds), the user says a command such as “re-factcheck” or “disagree.” The fact checking system is able to perform anautomatic review with different sources than used for the original factcheck and/or a manual review occurs. Then, the result of the re-factcheck is displayed (e.g., the fact check result has been confirmed ordisproved and a correction is provided). In some embodiments, there-fact check occurs automatically, and the result is displayed inreal-time. In some embodiments, the result is displayed before the endof a show/event. In some embodiments, the re-fact check is sent to auser's mobile device via text message or email at a later time. Themanual review is able to include sending a fact check result to anentity for manual review and receiving a result from the entity.Statistics are able to be gathered, maintained, and displayed of howoften fact checked comments are challenged, proven wrong, provencorrect, and/or any other statistics. The statistics are able to begathered in any manner (e.g., manually, automatically, or a combinationthereof). In some embodiments, the statistics are indicated when a userrequests the information. In some embodiments, the statistics areindicated when the fact checking system is referenced (e.g., commentatormentions the fact checking system). The statistics are able to beindicated in any manner described herein (e.g., at the bottom of atelevision screen or on a smart phone in real-time). In someembodiments, the statistics of the fact checking system are displayed ina comparison format with a network and/or other entity. In someembodiments, justifications as to why the fact checking system was wrongare provided (e.g., system glitch that has been fixed), sources thatprove the fact checking system wrong are provided, and/or any otherinformation to inform the user that the fact checking system is notbiased. A searchable data structure is implemented to store some or allof the fact checked data and statistics, including re-fact checkedinformation, so that users are able to search and verify the factchecked information. The fact checked information is stored in anymanner, such as searchable by topic, by entity, by date, and/or anyother way. In some embodiments, the fact checking system indicates alabel of the specific implementation of the fact checking system such as“unbiased fact checking system” or “Bob's personalized fact checkingsystem” depending on the implementation. In some embodiments, the factchecking system invites users to disprove the fact checking system byproviding sources. In some embodiments, the fact checking system re-factchecks using the provided sources. In some embodiments, users are ableto rate the fact checked content, and in some embodiments, users areable to challenge or overrule the fact checking system. In someembodiments, challenging or overruling the fact checking system includesverifying a user's credentials and enabling a user to overrule orchallenge a fact checking result by selecting a result and providingevidence (e.g., a disagreeing source) of the inaccuracy of the result.Safeguards are able to be implemented to prevent manipulation of thesystem. For example, before being able to overrule the fact checkingsystem, each user is verified as unbiased by answering questions toprove a lack of bias, by receiving credentials, and/or any other method.In some embodiments, in addition to or instead of the user answeringquestions, information about the user is also ascertained manually orautomatically by reviewing/analyzing the user's blog, social networkinginformation and/or any other information. In another example, acommittee is formed with members from each political party who factcheck the fact checking system. In some embodiments, the fact checkingsystem compares and displays the accuracy of the fact checking systemwith other outlets, networks, and/or any other entity. The comparisonand/or display of the accuracy information is able to be performedautomatically and/or manually and is able to occur in real-time ornon-real-time. FIG. 33 illustrates an exemplary chart comparing theaccuracy of several entities according to some embodiments. In someembodiments, users are able to review the sources used in determining afact check result including sources that agree and sources thatdisagree. In some embodiments, when a user selects to review thesources, the user is taken to the exact page, cell in database, and/orother specific section of the source for efficiency. In someembodiments, only the specific section is available, and in someembodiments, the entire source is available. In some embodiments,sources are classified so that a user is able to select a specificclassification of sources. The classifications are able to be political(e.g., Conservative, Moderate, Liberal, Green, and others),agree/disagree, and/or any other classifications. For example, the factchecking system indicates, “President Z's statement about gas pricesbeing higher 4 years ago is misleading.” In some embodiments, a user isable to select to review only disagreeing sources to see why thestatement may not be misleading.

FIG. 34 illustrates a flowchart of a method of fact checking the factchecking system according to some embodiments. In the step 3400, factchecked information is flagged. The flagging is able to be performed byusers and/or automatically. In the step 3402, the fact checkedinformation is fact checked a second time (e.g., a subsequent fact checkoccurs after the first fact check). The second fact check is able to beperformed manually, automatically, or a combination thereof, asdescribed herein. In some embodiments, the second fact check usesdifferent sources than the first fact check. In the step 3404, theresult of the second fact check or verification fact check is indicatedin any manner as described herein. For example, a comment by Z states,“the economy is struggling because of the President's policies.” Thefact checking system determines that the economy is struggling becauseof cyclically weak demand. However, because a number of people above athreshold have flagged the comment, the fact checking system performsanother fact check using different sources. The second fact check againdetermines that there is no evidence that the President's policies arecausing the economy to struggle. The fact checking system then indicatesthat the fact check result has been confirmed. In some embodiments, thesecond fact check result is only indicated if the second fact checkresult is different than the first fact check result. In someembodiments, more or fewer steps are implemented, and/or the steps aremodified. For example, in some embodiments, the step of flagging is notincluded.

In some embodiments, the reliability of each source is determined byclassifying each source (e.g., a table or other data structure stores asource type and a corresponding rating: an encyclopedia is given arating of 10, a national newspaper is given a rating of 7, aninformational blog is given a 5, and an opinion blog is given a ratingof 1), comparing each source (other than sources rated as a 10) or partsof each source with higher rated sources, sources rated 10 are able tobe compared with other sources rated 10, comparing with other sources(e.g. equivalent or lower rated), determining how many sources agreewith the source, and/or determining how many sources disagree with thesource, and computing each source's reliability. For example,determining a source agrees with information is by comparing theinformation with the source and finding a matching result, anddetermining a source disagrees with information is when the comparisonof the information and the source does not find a match. A match is ableto be determined in any manner such as an exact text match, usingcontext, using natural language processing, and/or any manner. Anexample of a source agreeing with information is someone saying energyindependence is not a priority of the President, and a source includestext that says the based on past public statements, the President has nodesire for energy independence. An example of a source disagreeing withinformation is someone saying the President caused gas prices to rise,and a source specifies that the main reason for the gas price increaseis greater global demand for oil. In some embodiments, a source isparsed and each parsed segment is compared with other sources. Then,depending on how many sources agree with each segment determines how asource is rated. In some embodiments, the source is parsed for factchecking In some embodiments, the sources are classified automatically,manually or verified manually after automatically classified. In someembodiments, the reliability of sources is determined automatically,manually or verified manually after being determined automatically. Insome embodiments, the sources are stored in a data structure with thehighest rated accessible first in the structure. In some embodiments,some of the sources are classified manually, and then used forcomparison purposes to classify additional sources. For example, threedifferent encyclopedias are given a 10 rating, 5 different dictionariesare given a 10 rating, 7 mostly accurate news articles are given a 9rating, and 5 political opinion articles are given a 2 rating for beingmostly inaccurate. Then, additional sources are compared with thepreviously classified sources, and a rating is determined. In someembodiments, sources are searched for and given an initialclassification rating manually (e.g., by determining content is anencyclopedia, a personal blog), and then the fact checking systemautomatically generates the reliability rating using the initialclassification rating and the accuracy of the content. In someembodiments, sources are rated by peer review. In some embodiments,sources are rated using trending information. In some embodiments,sources are rated using historical information (e.g., analyzing archivesfrom a source). In some embodiments, the source ratings are updatedperiodically (e.g., daily, monthly, yearly) by checking newly presentedmaterial since the last check of the source information.

FIG. 35 illustrates a flowchart of a method of rating sources accordingto some embodiments. In the step 3500, a source is classified. In thestep 3502, the source or aspects of the source are compared with othersources. In the step 3504, a reliability rating is computed for thesource based on the comparison of the source with the other sources. Insome embodiments, more or fewer steps are implemented. For example, insome embodiments, before a source is classified, the source is preparedfor fact checking (e.g., searched for, input in to a fact checkingdatabase, and/or linked to a fact checking database).

In one example, a computation is the classification rating+(number ofagreeing higher rated sources/number of disagreeing higher ratedsources)*0.01 with a maximum of +1. Furthering the example, a nationalnewspaper is classified with a rating of 7, and based on comparisons ofmany stories in the newspaper with many sources, it receives a maximumaddition of 1 giving it a rating of 8.

In another example, a computation is the classification rating+(numberof segments with a number of agreeing sources above a threshold/numberof segments with a number of disagreeing sources above a threshold)*0.1with a maximum of +1. Furthering the example, an informational blog isclassified with a rating of 5, and the blog is parsed into 1000 factcheckable segments. Eight hundred of the segments are each verified asvalid by at least 10 (e.g., threshold) other sources. One hundred andninety of the segments are each verified as invalid by at least 10 othersources. Ten segments are not verified as either valid or invalid, alsoreferred to as unknown. The computation is 5+(800/190=4.2)*0.1=5.42.

In another example, a computation begins with the initial classificationrating which is then increased by 2 points with a cap at 10 if a veryhigh percentage (e.g., 99%) of the segments are verified as accurate bya threshold of higher rated or equally rated thresholds. The rating isincreased by 1 point if a high percentage (e.g., 90%) of the segmentsare verified as accurate by a threshold of higher rated or equally ratedthresholds. The rating is decreased by half of the initialclassification point if a moderate percentage (e.g., 30%) of thesegments are verified as inaccurate by a threshold of higher rated orequally rated thresholds.

In some embodiments, monitoring includes monitoring closed captioninformation which is in text form. The closed caption information isthen able to be fact checked as described herein.

In some embodiments, a data structure is populated for being searchedfor fact checking and/or supplemental information. A crawler is able tofind and retrieve data to store. Information is able to be input byusers, media and/or any others. Previously checked facts are stored in adatabase. The fact checking system is able to preemptively fact checkwebsites, archived information, and/or any other information to populatethe database. The fact checking system is able to check websitesspecifically set up for fact checking and/or supplemental information toretrieve data for fact checking and/or supplemental information. Thedata structure is able to be populated with advertisement data andcorresponding advertisement data (e.g., competitor's advertisements).The advertisement data is able to be input by users and/or companies.Any other data described herein is able to be acquired in any manner topopulate the data structure.

In some embodiments, a vehicle (e.g., car, truck, boat, motorcycle)includes a display on a windshield, window, dashboard, seat, ceiling,roof, and/or any other component of the vehicle. The display is able tobe implemented in any manner including, but not limited to a projectiondisplay, an LCD display and/or any other display. In some embodiments,the display on the windshield utilizes tinting, ice, dust, dirt, or aspray of water on the outside of the windshield to enable a projectionof a video and/or image to be displayed. In some embodiments, thevehicle is equipped with a camera or other scanning device to scan itemssuch as billboards, store names, street signs, and/or any otherdisplayed information. In an example, the camera scans a store name, andthen displays on the windshield and/or dashboard, supplementalinformation regarding the store including, but not limited to, hours,prices of items, controversies involving the store, ratings of thestore, fact check information, and/or any other information. In someembodiments, the vehicle operates in conjunction with a user's mobiledevice. For example, the vehicle's camera scans a store name, andsupplemental information is displayed on a user's mobile device and/oradded to a contacts list. In another example, a motor home camera scansan item (e.g., billboard), and then displays supplemental information ona television inside the motor home. In some embodiments, a user inputsan item to search for, and the vehicle camera searches for store names,determines items at the store (e.g., by searching a database and/orwebsite for the store), and informs the user when the item is found. Forexample, a user is looking for a baseball bat, and when the vehiclecamera detects Sporting Goods Store X, the vehicle camera indicates onthe dashboard that the item has been found. In some embodiments, thevehicle system is able to be used to fact check and/or providesupplemental real estate information, including, but not limited to, ahouse address, size, number of rooms, age, price, how long for sale,current mortgage, current property tax bill, photos of inside/outside,listing agent, comparable sales/listings, trends, neighborhoodinformation (e.g. crime, population), school information, and/or anyother information. In some embodiments, the glasses and/or otherclothing described herein are able to be implemented in conjunction withthe vehicle system or in a similar manner as the vehicle system. Forexample, the vehicle camera detects a store name, and the supplementalinformation is displayed on the user's glasses.

FIG. 36 illustrates a vehicle with fact checking capabilities accordingto some embodiments. The vehicle 3600 includes any standard vehiclecomponents as well as a display 3602, a camera/scanning device 3604, anda computing device 3606. As described above, the display 3602 is able tobe any display including a display on the windshield. Thecamera/scanning device 3604 is able to be located anywhere on thevehicle 3600 and is used for scanning objects such as store names,buildings and/or any other objects. The computing device 3606 is able toprocess the information acquired by the camera/scanning device 3604including fact checking the information as described herein and send theresults to the display 3602. In some embodiments, the camera/scanningdevice 3604 is wirelessly coupled to a user's mobile device 3608 whichprocesses the acquired data and is able to transmit the result to thedisplay 3602. Although various components are included in the example inFIG. 36, more or fewer components are able to be utilized.

In some embodiments, the vehicle fact checking system is utilized bypolice and other law enforcement. The camera is able to be used to scana license plate and/or a type of car and by converting and/or comparingthe acquired data with one or more databases, determine if the car isstolen, if the person has an outstanding warrant or a suspended license,and/or any other information useful to the police. In some embodiments,the information is useful for non-law enforcement people, for example,for recording information about an accident or a crime.

In some embodiments, the fact checking system is able to be used to factcheck forms, contracts and other documents. For example, legal documentsare fact checked to ensure the name, address, and/or any otherinformation is accurate. The documents are able to be parsed intofact-based portions and law-based portions. The fact-based informationis fact checked by comparing the information with information in apublic database, private database, and/or any other documents orinformation. For example, if eight documents spell the person's name“Brian,” and then his name is spelled “Brain” in the other twodocuments, by comparison, the user is alerted that his name different intwo of the documents. In some embodiments, the law used in the documentsis fact checked. The law is checked to make sure it is not stale. Thelaw is able to be checked by comparing the language with current codesections publicly available and/or in any other way. In another example,privacy notices and other legal text (e.g., on a website) are analyzed,and transformed into lay terms, and/or specific elements are highlightedfor a user. For example, when a user logs on to a website, the terms andprivacy notice are summarized and/or specific sections are highlightedfor a user in a pop-up window. The summary is able to be a summaryprepared in advance manually or an automatically analyzed summary. Thehighlighted sections are able to be manually highlighted in advance orautomatically highlighted by searching for specific phrases or keywords.The summary and/or highlighting is stored so that when a user logs ontothe website, the summary and/or highlighting is retrieved and displayedfor the user.

In some embodiments, the fact checking system is able to be used to factcheck images, videos, sounds, and/or any other content. The content isable to be fact checked by analyzing a first content, searching for asecond content, and fact checking the first content by comparing thefirst content with the second content. For example, the fact checkingsystem is able to determine if the content has been doctored and/ordetermine the age, location, and/or other information of the content todetermine the accuracy of the content. Whether the content has beendoctored is able to be determined by searching for similar content andcomparing the content to determine if there are any changes between thecontent. For example, a photo shows a person with an illegal item in hishand, but by using an image comparison implementation, five photos showthe same photo without the item in his hand, it is able to be determinedthe photo has been doctored. In some embodiments, a verification processis implemented to ensure the additional photos are valid and not thedoctored ones. In some embodiments, the quantity of photos is used asthe verification process. For example, if there is only one photo withthe item in the person's hand, and there are 1,000 photos found onlinewith no item, then the 1,000 photos are deemed to be valid. In someembodiments, the verification process is manually performed. In anotherimplementation to determine doctoring of content, the content isanalyzed to determine if there are any edits. For example, animplementation is able to determine if any edges are improper whichindicate doctoring. Any other doctoring detection implementations byanalysis of the content are able to be used. In some embodiments,doctoring is determined by searching and comparing and by contentanalysis. In some embodiments, the content is fact checked by analyzingthe embedded content information (e.g., exif information). For example,if the content is purported to be from 2012 (e.g., caption of photo says“Celebrity X at the beach, yesterday”), but the embedded informationindicates the photo was taken in 2008, then the fact checking system isable to determine the misinformation and indicate a correction and/orany other notification to the user. In some embodiments, the content isfact checked by searching for a content match in a database. Forexample, a database stores photos, dates of the photo, and/or any otherrelevant information. The database is searched for the photo inquestion, and the date and/or other information is compared with theasserted information (e.g. date mentioned in caption), and if the datesdo not match, a notification is indicated.

In some embodiments, dual mobile devices are utilized for fact checking.For example, two separate arm/wrist devices (e.g. watches) are usedwhere one displays the content (e.g. broadcast information), and thesecond device displays fact checking and/or supplemental information. Inanother example, a device is worn on the arm, and a second device isworn in/near the ear. In another example, a device is worn on the arm,and a second device is worn on/near the eyes. In another example, adevice is in/part of a vehicle, and a second device is a mobile device.In another example, a mobile device and an airplane display are used inconjunction. For example, the airplane display displays news, and themobile device fact checks the news and displays the fact checkingresults, or vice versa. Any combination of the devices is able to beimplemented. Any display and/or transfer of information is able to beimplemented. Additionally, more than two devices are able to be used incombination.

In some embodiments, political advertisements are classified as positiveor negative. The classification is able to be performed automatically ormanually. The data such as the number of positive and negativeadvertisements is maintained (e.g., stored in a data structure), andthen displayed or retrievable for users. For example, when a candidateis detected, supplemental information indicating percent positiveadvertisements and percent negative advertisements by/for the candidateis presented.

In some embodiments, autofill, such as automatically suggesting a searchstring in a search engine, utilizes fact checking for determining theautofill suggestion or suggestions. For example, when a user inputs partof a search string, “Texas is the largest,” without using fact checkingin conjunction with the current autofill implementation, the suggestionsinclude “Texas is the largest state in the united states,” “Texas is thelargest state” and other suggestions. However, these suggestions arefactually inaccurate. Therefore, using fact checking in conjunction withany autofill implementation, a suggestion would be more factuallyaccurate such as “Texas is the largest state in the continental unitedstates.” In another example, the autofill would change the search stringfrom “Texas is the largest” to “Alaska is the largest state.” In someembodiments, the autofill with fact checking implementation is performedby first performing an autofill analysis and performing a fact check asdescribed herein and based on the fact check, changing the autofillresult. For example, a user inputs, “Texas is the largest.” The autofillanalysis determines that “Texas is the largest state in the unitedstates” is the primary suggestion. The autofill suggestion is then factchecked, and the result of the fact check is returned which modifies theautofill suggestion to state, “Texas is the largest state in thecontinental united states.” The process is able to occur automaticallyso that the user does not see the initial un-fact checked suggestion andonly sees the fact checked suggestion. In some embodiments, multipleresults are returned from the fact check and are each used to modify theinitial autofill suggestion or suggestions. In some embodiments, eachinitial autofill suggestion is fact checked and modified. The autofillanalysis and suggestions occur in real-time while the user is typing. Insome embodiments, the autofill analysis and fact checking occurssimultaneously or in parallel. Fact checking is able to be used in asimilar manner with predictive text.

FIG. 37 illustrates a flowchart of a method of using fact checking withautofill information according to some embodiments. In the step 3700, anautofill determination is performed. In the step 3702, a fact check ofthe autofill result is performed. In the step 3704, an updated autofillresult is displayed. In some embodiments, more or fewer steps areimplemented. In some embodiments, the order of the steps is modified.

In some embodiments, the fact checking system is used in conjunctionwith social advertising where an advertisement is based on what“contacts” are viewing/writing/doing.

In some embodiments, a fact checking and summarizing system isimplemented for fact checking and/or summarizing what a user iswatching/listening to or is not watching/listening to but is interestedin. In some embodiments, the fact checking and summarizing system isimplemented for other items (e.g., although user is not interested inpolitics, a summary of the presidential race is generated and displayedfor the user). The fact checking and summarizing is able to occur inreal-time while the event occurs. For example, a user inputs that he isinterested in the upcoming State of the Union speech or the Presidentialdebate. The fact checking and summarizing system monitors theinformation independently from the user (e.g., a third party devicemonitors any or all broadcast information) and then provides updates ona user device (e.g., text on the bottom of a television screen, an SMSmessage or tweet on a user's mobile phone, a video/audio clip on theuser's mobile phone or any other indication described herein). In someembodiments, the updates are periodic (e.g., every 5 minutes) and/or theupdates are when a highlight occurs. Highlights are able to be detectedin any manner such as when applause is detected, when an error isdetected by fact checking, when a designated highlight is detected, whena user (e.g., operator, news producer) marks a section as a highlight,and/or any other detection. In some embodiments, the fact checking andsummarizing occurs in real-time but is stored for later playback to theuser. The updates are able to include summarized aspects of the content,misinformation with corrected information, biased information, and/orany other information. In some embodiments, the updates includeinformation related to a manually input or automatically selectedkeyword, search phrase, or topic. For example, a user only wants updatesabout the economy in the State of the Union speech, the fact checkingand summarizing system is able to detect keywords related to the economysuch as taxes, debt and deficit and present a summary or video/audioclip of the specified topic. In some embodiments, the presented updateincludes a few seconds (e.g., 5, 10 or 30 seconds) of video (orequivalent text) before the detected keyword to ensure adequate context,and then a set period of time (e.g., 30 or 60 seconds), continuous playuntil the user stops the update, or another implementation toautomatically detect a stop (e.g., detecting a change of topic toanother topic by detecting a keyword for a different topic). In someembodiments, although the presented video or text in the update beginsat a set point, the entire video or text is provided to enable a user togo back further if needed or desired. In some embodiments, the summaryis able to be manually reviewed for accuracy. In an example, thesummarizer summarizes specific points such as how the economy is doingby indicating the stock market is up over X years, unemployment is downto Y, GDP growth is at Z %. Current rates and/or current trends are ableto be included in the summary. In some embodiments, the summarizingdisplays a summary of the fact checking results at the end of a show orevent.

FIG. 38 illustrates a flowchart of a method of fact checking andsummarizing according to some embodiments. In the step 3800, informationis monitored as described herein. In the step 3802, the information isprocessed as described herein. In the step 3804, the information is factchecked as described herein, and the information is summarized. In thestep 3806, the fact checking results and summary are updated on a user'sdevice. In some embodiments, more or fewer steps are implemented. Insome embodiments, the order of the steps is modified. In someembodiments, the some of the steps are performed separately.

In some embodiments, a fact checking system is able to detectmanipulation of a source intended to generate a higher reliabilityrating. For example, if the reliability rating is determined based onthe accuracy of a source or segments of a source, the source couldinclude an encyclopedia worth of data at the bottom of the source, butinclude opinion information at the top of the source. Furthering theexample, a blog could include factually accurate information insmall/hidden text at the bottom of each web page, but at the top of eachweb page include inaccurate and/or biased information. The fact checkingsystem is able to prevent such a manipulation in any manner. Forexample, the fact checking system is able to separate a source intoportions, and if one portion is factually inaccurate (e.g., bydetermining many segments in the portion to be disagreed with by othersources), and another portion is factually accurate, the source isseparated into two sources and each is classified separately. In anotherexample, the source is compared with other sources to determine ifcopying has been performed (e.g., blog copied a thousand lines of textfrom encyclopedia), and any copied content within the source is excludedfrom the reliability determination of the source. In some embodiments,metadata of a source is analyzed. In some embodiments, sources aremanually checked to determine if any manipulation has occurred. In someembodiments, a penalty is paid if manipulation is detected to deter anymanipulation. For example, a reliability rating of a source is droppedto 0 or 1 out of 10, if manipulation is detected. In some embodiments,rewards are awarded for detecting manipulation of a source. In someembodiments, an alert is made to suggest a manual check if a sourcereceives an unexpectedly high rating (e.g., above a threshold)automatically. For example, a source is classified as a personal opinionblog, and it receives a 100% accuracy rating from the automatic ratingsystem. An alert is sent for a person to do a manual review of the blogand/or an additional automatic review is performed. In some embodiments,users are able to request a check for manipulation of a source bysubmitting source identification information to a manipulation detectionsystem. In some embodiments, other forms of manipulation are able to bedetected. For example, if a user generates a web page that containsfactually inaccurate information, and then generates 50 duplicate webpages with different names, URLs, and/or other identifiers, the sourcesare able to be compared and determined to be a single source and notgiven weight of 50 different sources. In some embodiments, reliabilitydetermination utilizes other methods of determining reliability such asthe number of other sources that link to a web page or web site.

FIG. 39 illustrates a flowchart of a method of detecting manipulation ofsources according to some embodiments. In the step 3900, a source isanalyzed for manipulation. For example, the source is parsed, eachsegment is compared with other sources to determine accuracy, eachsegment is compared with other sources to determine copying, the sourcerating is analyzed, and/or the size and/or color of the text is analyzedto determine if information is hidden. In the step 3902, an action istaken on the source based on the analysis. For example, the sourcerating is dropped to a lowest level if manipulation is detected or thesource rating is maintained if no manipulation is detected. In someembodiments, more or fewer steps are implemented. In some embodiments,the order of the steps is modified.

In some embodiments, a checklist or timeline of campaign promises isgenerated. The checklist or timeline is able to be generatedautomatically and/or manually. For example, candidate statements aremonitored, and when a campaign promise is made, the promise is added tothe list. In another example, a user manually inputs items in achecklist. Then, after the candidate wins the position, the promises aretracked while he is in office. When an item on the checklist iscompleted, it is indicated as completed on the checklist. Determiningthe item is completed is able to be performed automatically and/ormanually. For example, broadcast information is monitored forinformation (e.g., keywords: “Unemployment below 6%”) indicating theitem has been completed. Completed and uncompleted items are able to bedisplayed. In some embodiments, a justification is included as to whythe item has not been completed (e.g., a Republican president with aDemocratic Congress reluctant to compromise). The justifications areable to be determined automatically and/or manually. In someembodiments, a likelihood of success of completing the item is indicatedduring and/or after the campaign. The likelihood of success is able tobe determined using any factor such as the current and/or projectedmembers of the government, popularity of the item with the population,and/or any other factor. In some embodiments, fact checking isimplemented with the campaign promise checklist or timeline. Forexample, if a comment from someone who is not the candidate is used togenerate a campaign promise, the comment is fact checked to determine ifit should be considered a campaign promise. Furthering the example,Commentator states that Candidate A promised to end the wars, and thecomment is fact checked (e.g., by comparing the comment with an actualcomment from the Candidate), and if the comment is taken out of context,then the comment is not added to the checklist. Other aspects of thecampaign promise checklist are able to be fact checked as well.

FIG. 40 illustrates a flowchart of a method of implementing a checklistof campaign promises according to some embodiments. In the step 4000, acandidate statement is monitored. In the step 4002, the candidatestatement is processed (e.g., parsed for a campaign promise). In thestep 4004, the campaign promises are tracked in a checklist. In the step4006, when a campaign promise is detected as completed, the checklist isupdated. In some embodiments, more or fewer steps are implemented. Forexample, fact checking is incorporated. In some embodiments, the orderof the steps is modified.

In some embodiments, a salary or amount of money paid to a contributoris displayed when the contributor is recognized. For example, whencommentator A appears, text is displayed that says, “Commentator A is apaid contributor by X and is paid $1M yearly by X.” Contributor is ableto be recognized in any manner described herein such as by facerecognition and/or voice recognition. Indicating is able to be anymanner described herein.

In some embodiments, a voting fact checking system is implemented toprovide a user with voting information. For example, the system providesa user with the address of the voting location, directions to thelocation, a countdown of when to vote, an alert to vote on election day,how/where to register to vote and other information regardingregistering to vote, a summary and/or analysis of the issues and/orcandidates based on fact checking and/or other analysis during thecampaign and/or before, suggestions on whom to vote for and/or what tovote for, and/or an explanation of how items (e.g., propositions),positions, and/or candidates would affect the user's life, relatedpeople's lives (e.g., contacts based social network information), otherpeople's lives, the user's state, the user's country, and/or the planet.For example, the system indicates that Candidate A's plan to cut taxeswill save the specific user $2000/year based on his current salary. Insome embodiments, a user's input, acquired information (e.g., fromsocial networking sites) and/or determined importance as describedherein is able to be used to determine how the user would be affected.For example, it is determined that a user has a salary of $30,000 peryear (which is determined to be the most important item to the user),but is socially conservative (although not vehemently), and Candidate Awants to cut taxes, but the cut will not affect someone with such asalary, the tax cut will likely add to the country's debt, but thecandidate is against gay marriage which does not affect the personpersonally. Therefore, it is indicated to the user that Candidate A'sgoals are not in line with the user's most important items. FIG. 41illustrates an exemplary voting fact checking app according to someembodiments. Voting information presented to the user is also able toinclude main points/positions of each candidate, projections of futurelaws and other effects based on the candidate's plans/positions,contribution information (e.g., how much, by whom), superPAC information(e.g., contributors and how much), and/or any other information. Factchecking information is also included, such as misinformation providedby the candidate, associates/supporters of the candidate, news membersdiscussing the candidate, superPACs, other organizations supporting thecandidate and/or advertisements for or by the candidate. In someembodiments, the summary of candidates and/or other politicalinformation is sent to only registered voters. In some embodiments, thesummary of candidates and/or other political information is sent to onlyregistered voters who did not vote in the last election. In someembodiments, the summary of candidates and/or other politicalinformation is sent to only unregistered voters. Determining who to sendthe summary information to is able to be based on public records, socialnetworking information, and/or any other manner. In some embodiments, asummary includes how each choice could affect the user. For example, asummary states: Candidate A is a Republican focused on lowering taxes,increasing jobs, and reducing government regulations, and based on yourinformation, Candidate A's policies may help you find a job, but notmuch more; Candidate B is a Democrat focused on increasing taxes onsome, increasing jobs, maintaining government regulations includingenvironmental protections, and based on your information, Candidate B'spolicies may help you find a job and protect the environment which isimportant to you.

In some embodiments, a table or other structure is presented comparingthe main points of the candidates. In some embodiments, the table isbased on and/or includes fact checking results. In some embodiments, thetable includes additional information such as comparisons of politicaladvertisements. FIG. 42 illustrates an exemplary table of a candidatecomparison according to some embodiments.

In some embodiments, the voting fact checking system suggests anadvertisement and/or other content for the user to watch, read and/orlisten to. The suggestion is able to be based on the user's politicalaffiliation (e.g., registered Democrat), importanceselections/determination as described herein, personal information,social networking information, and/or other information. In someembodiments, the suggested content includes only fact checked content(e.g., an advertisement that has been validated as true by the factchecking system or an advertisement that includes real-time factchecking information to point out misinformation and/or bias). In someembodiments, a suggestion is made to avoid specific content (e.g.content determined to contain false information). For example, if a useris still undecided on whom to vote for, and the environment is mostimportant to the user, the voting fact checking system is able tosuggest a web page that shows Candidate B's voting record of beinganti-environment, and Candidate A's pro-environment video clip. In someembodiments, a list of all advertisements, speeches, summaries ofspeeches, and/or any other content from one or multiple candidates ispresented (e.g., a playlist). In some embodiments, advertisements byopposing candidates are presented in a side-by-side view or one afterthe other for comparison purposes. For example, Candidate A'sadvertisement about “jobs” is presented including fact checkinginformation, and then Candidate B's advertisement about “jobs” ispresented with fact checking information. In some embodiments, theeffects on the user are displayed in an order with the most importantaspect displayed first or at the top of the list and less importantitems displayed down the list.

In some embodiments, the voting fact checking system provides a userwith statistics on whether his vote will affect the outcome. Forexample, if a user is a Republican in California, unless the Democratcandidate has major flaws, most likely the user's vote for Presidentwill not affect the outcome of the election due to the Electoral Collegesystem and the fact that California typically votes Democrat. Therefore,the statistics would indicate that the user's vote is not likely toaffect the outcome of the Presidential election. On the other hand, ifthe user is a voter in Ohio, where outcomes have been decided by a smallmargin, the statistics indicate that the user's vote may affect theoutcome of the election. Determining if a user's vote will affectelection is able to be by analyzing historical information (e.g., pastelections), current polling information, and/or projections (e.g., theprojected electoral map). The indication of whether the user's vote willaffect the outcome is able to be implemented in any manner describedherein such as using different color coding based on the potentialeffect.

In some embodiments, the voting fact checking system matches and/orsuggests a candidate, proposition selection, and/or any other votingitem based on user selections, importance to the user, personalinformation, social network information (e.g., a user's Facebook® page,tweets, blogs, or contacts' pages, tweets, blogs), and/or any otherinformation as described herein. In some embodiments, the matching orsuggestion is impartial, and in some embodiments, the suggestion isbiased. In some embodiments, the voting fact checking system provides adescription and additional information of third party candidates.

In some embodiments, the voting fact checking system utilizesautomatically and/or manually generated summaries as described hereinand/or generated playlists (e.g., of political advertisements). In someembodiments, the advertisements, videos and/or other content are storedin a data structure (e.g., database). In some embodiments, the datastructure is populated during and/or before the campaign on a continuousbasis (e.g., updated periodically or when a new video, clip oradvertisement is detected), and in some embodiments, the data structureis generated near election time by crawling for content. The datastructure is able to be configured in any manner, for example,separating pros and cons for each candidate, separating the datastructure into advertisements, videos, speeches, and other content,separating the data structure into factually accurate, factuallyinaccurate, and misleading, including differently levels of accuracy,inaccuracy, and misleading.

FIG. 43 illustrates a flowchart of a method of voting fact checkingaccording to some embodiments. In the step 4300, a user isdetected/determined/identified. In the step 4302, voting information isprovided to the user. In the step 4304, an advertisement (or othercontent) is suggested based on the user. In some embodiments, a votingitem is matched/suggested. In some embodiments, the content is providedto the user, or access to the content is provided. In some embodiments,more or fewer steps are implemented. In some embodiments, the order ofthe steps is modified.

In some embodiments, the voting fact checking system includes aninterface to enable a user to ask a question and/or search for a topic(e.g., what is Candidate A's position on taxes?).

In some embodiments, the voting fact checking system enables the user toinput a candidate (e.g., I want to vote for Candidate A), and thecandidate is fact checked and compared with user information (includingimportance information) to determine if the candidate's views match withthe user's views.

In some embodiments, the user is able to manually input information forthe voting fact checking system to determine which candidate the user ismost aligned with. For example, the user is able to answer a set ofquestions, and the voting fact checking system determines a possiblecandidate for the user.

In some embodiments, a simplified voting fact checking system operatesautomatically by determining the user based on mobile device data (e.g.,cellular phone number), determining additional information about theuser (e.g., searching social network information, blogs, personalinformation such as salary, job type, and taxes paid in previous years),comparing the information about the user with the candidate positions,likely positions, values, and/or goals, status of the country and/or anyother information, and generating a result suggesting a candidate tovote for or indicating a candidate with views aligned with the user. Forexample, after the user initiates a mobile device app, the simplifiedvoting fact checking system performs its tasks automatically anddisplays, “Based on the information I have about you, Candidate C'sviews are most aligned with yours.” In some embodiments, a selectableoption is included to allow the user to view more information (e.g.positions of the candidate, personal information used for selecting thecandidate and/or any other information). In some embodiments, pros andcons of each candidate are presented based on the user (e.g., userinterests, importance, and/or other personal characteristics). In someembodiments, fact checking information is taken into account. Forexample, if Candidate C has been found to have lied or misrepresentedinformation, this information is used when making a suggestion. Inanother example, if a candidate flip-flops often, he may not betrustworthy, which affects whether he should be recommended. In someembodiments, a user is automatically determined based on phone number,location, IP address, email address, and/or any other information thatidentifies the user for purposes of providing voting fact checkinginformation.

FIG. 44 illustrates a flowchart of a method of voting fact checkingaccording to some embodiments. In the step 4400, a user isdetected/determined/identified. In the step 4402, additional informationis determined about the user. In the step 4404, the user information iscompared with candidate information. In the step 4406, a result of thecomparison is generated and indicated. In some embodiments, more orfewer steps are implemented. In some embodiments, the order of the stepsis modified.

FIG. 45 illustrates an exemplary table of news coverage analysisaccording to some embodiments. The fact checking system as describedherein is able to determine the number of inaccuracies, number ofadvertisements shown for each candidate, number of stories for/againsteach candidate, number of misleading stories and/or any otherinformation for each network/entity.

In some embodiments, contradictory arguments/positions are indicated.For example, under President A, Commentator X says, “let's give thePresident a little more time to fix the economy,” but for President B,Commentator X says, “the President's plans are not working ” A clip ofthe comments about President A by the commentator are displayed inconjunction with or after the comments about President B. In someembodiments, an indication of “contradiction” is displayed as well. Thecontradiction is able to be determined automatically or manually. Forexample, a data structure is able to be populated with comments (orlinks to content) made by Commentator X about President A, and in acorresponding column, contradictory comments are included. In anotherexample, the fact checking system searches for and compares source datato determine if a contradictory statement is being made. For example,the fact checking system searches a database of all comments made byCommentator X regarding a specific topic, finds a relevant comment,retrieves the comment and sends a text message to the user's deviceindicating what Commentator X said in the past about the topic.

In some embodiments, issues discussed by achannel/station/commentator/show/any other entity are tracked andstored. For example, political show X discussed the economy and debtmost often in 2009, but rarely mentioned the economy and debt in 2008.Included with the tracked issues are dates, possible reasons why therewas a change in topics (e.g., war ended), number of times discussed,positive, neutral or negative discussion of the topics, and/or any otherinformation. The tracking and storing is able to occur manually and/orautomatically. The tracked information is then able to be used foranalysis and/or presented to indicate bias or other analysis.

In some embodiments, a personal fact checking system tracks contacts'(e.g., friends') factual accuracy, bias, and/or other characterizations.The personal fact checking system monitors communications of thecontacts (e.g., phone calls, blogs, message boards, emails, textmessages, social networking sites), analyzes the communications (e.g.,determines/detects the user, processes, fact checks, determines biasand/or any other analysis described herein), and displays an icon (orother graphical representation) representing the contact'scharacteristics including factual accuracy, bias, and/or othercharacterizations in real-time or in non-real-time. In an example, amobile device displays a contact list where each contact has abackground based on their factual accuracy, bias and/or othercharacterization. For example, Contact A has a green background becausehe generally tells the truth, and Contact B has a red background becausemany of his comments have been determined to be false. In someembodiments, if the ratio of lies (or misinformation) to non-lies isabove a threshold, the background or icon changes. In another example,Contact C forwards factually inaccurate emails to friends, so ContactC's background changes to red. In some embodiments, if the number oflies or misinformation goes above a daily, monthly, or another timeframe threshold, then the background or icon changes color. In someembodiments, the monitoring, processing, fact checking, and indicatingoccurs on one or more devices. For example, a first device monitors,processes, and fact checks communications from users, and then resultsare sent to the user's device for indicating the background or iconchanges. In some embodiments, the results indicate the contact and aneffect of the contact (e.g., +/−accuracy). In some embodiments, when auser receives a phone call, SMS message, or other communication, thecaller's validity rating is displayed on the receiver's mobile phone.The validity rating is retrieved using the caller's mobile phone numberor other identifying information. For example, a database stores mobilephone numbers and corresponding user validity ratings. The phone of therecipient displays the validity rating in any manner (e.g., along withother identifying information).

FIG. 46 illustrates a flowchart of a method of fact checking contactsaccording to some embodiments. In the step 4600, communications of thecontacts are monitored. In the step 4602, the communications areanalyzed. In the step 4604, an icon representing the contact isdisplayed. In some embodiments, more or fewer steps are implemented. Insome embodiments, the order of the steps is modified.

FIG. 47 illustrates a diagram of a graphical user interface of factchecked contacts according to some embodiments. A list of contacts isdisplayed and next to each contact is an icon representing the factualaccuracy of the contact. In the example, a down arrow 4700 is used toindicate the contact has a negative factual accuracy (e.g., the contacttells more lies than a threshold), and an up arrow 4702 is used toindicate the contact has a positive factual accuracy. In someembodiments, an additional icon is displayed indicating the contact'sbias and/or any other characterization.

FIG. 48 illustrates a block diagram of furniture used in conjunctionwith fact checking The furniture is able to be any type of furniture,for example, a chair. The chair 4800, includes a signal receivingcomponent 4802 for receiving a signal from another device, a processingcomponent 4804 for processing the signal received, a vibration mechanism4806 for providing vibrations to the furniture, and a motion mechanism4808 for moving the furniture. As described above, the chair 4800receives a signal from a smart phone or television based on a result ofa fact check which causes the chair 4800 to vibrate when misinformationis presented, to tilt one way or the other when bias is detected (e.g.,left for liberal and right for conservative), to rock when a lie isdetected, and/or any other effect. The furniture is able to includefewer or more components than shown in the figure. The effects are ableto occur in real-time in conjunction with broadcast information and/orother information.

In some embodiments, the fact checking system is implemented torepeatedly fact check a specified item. For example, a comment thatstates, “the polls show the President is trailing” may be true, false,or unknown depending on when the fact check is performed. In anotherexample, a commentator states, “it is rumored, Candidate X is droppingout of the race.” Initially, a fact check may return unknown, but byrepeatedly fact checking, a result may be determined. In someembodiments, when a result of true or false (or confirmed) is returned,an alert is indicated that the rumor has been confirmed or not. In someembodiments, even when a result is determined the fact checking systemcontinues to fact check for a period of time in case the result changes.In some embodiments, tracking the information is able to be automatic,and in some embodiments, parameters are able to be set to check. In someembodiments, a notification is indicated with a result that a futurecheck will be performed.

In some embodiments, a GUI for rating articles so others are able tofilter the articles is implemented. For example, users are able to ratearticles as informative, funny, biased, accurate, inaccurate, aclassification (e.g., sports, economy, environmental), and/or any otherrating. In some embodiments, fact checking results of the articles areused to generate a rating or for searching. For example, a user searchesfor articles with a high funny rating and also a high accuracy ratingbased on the fact checking.

In some embodiments, a second device for receiving fact checking resultsand/or supplemental information is implemented. For example, the deviceis a display capable of receiving information transmitted from anotherdevice (e.g., a smart phone or tablet). The information is able to betransmitted in any way (e.g., Bluetooth®, Wi-Fi).

In some embodiments, user verification is performed by fact checking.For example, an entry page asks a user factually-based questions, andthe answers input by the user are compared with source information wherethe source is personal to the user (e.g., a social network page such asa Facebook® page, personal blog, private webpage).

In some embodiments, a window is automatically shrunk to a smallerwindow when inaccurate or misleading information is detected, and thenthe remainder of the screen is used to display the fact checkinginformation. FIG. 49 illustrates an exemplary changing of a window sizeaccording to some embodiments. Initially, the screen includes onlyadvertisement) 4900, but after a real-time fact check is performed, andthe advertisement is determined to be misleading, the advertisement)4900 is shrunk to a smaller window 4900′, and the remaining screen space4902 is used to display the fact checking information (e.g., a resultthat indicates the advertisement is misleading). In some embodiments,when an advertisement makes untrue or misleading comment, theadvertisement is shrunk, and a second or rebuttal advertisement isdisplayed. In some embodiments, the second advertisement is acompetitor's advertisement. In some embodiments, supplementalinformation as described herein is displayed in the remaining spaceafter the original content is shrunk to a smaller window. Shrinking thewindow size and displaying additional information is able to be appliedto any information, not only advertisements. For example, a news programwindow is temporarily shrunk while fact checking results and/orsupplemental information is displayed in real-time, and then after aperiod of time (e.g., 5 seconds), the news program is restored, and thefact checking information is shrunk, is moved (e.g., to within the newsprogram window), or disappears.

In some embodiments, a myth clarification implementation is utilized.FIG. 50 illustrates a flowchart of a method of myth clarificationaccording to some embodiments. In the step 5000, myths are stored in adata structure (e.g., database) including whether the myth is confirmed,possible, disproved, unsure or similar terms. For example, a databaseincludes the myth that “sitting too close to the television will hurtyour eyes,” with the result “disproved” and sources or cites to sourcesthat support the result. In the step 5002, a myth is detected (e.g., bycomparing monitored data with the stored myths). In the step 5004, thevalidity of the myth is displayed. The myth clarification implementationis able to be used by monitoring any communication described herein(e.g., monitoring a television broadcast or monitoring a user'sconversation). In some embodiments, the order of the steps is modified.In some embodiments, more or fewer steps are implemented.

In some embodiments, an interactive fact checking system is implemented.For example, a user is watching television, the fact checking systemindicates a comment was false, the user is then able to respond with acommand or question such as “why?” or “prove it” or “more information.”Depending on the command or question, the fact checking system respondswith citations proving why the comment was false or additional context.Any command or question is able to be utilized. For example, the user isable to ask for “only supporting sources,” “show me only disagreeingsources,” “show me only conservative sources,” “show me the full video.”A user is able to request and receive supplemental information from theinteractive fact checking system. For example, the user sees acommercial which is fact checked, and the user says, “show me a coupon,”and a digital coupon is presented on a user's smart phone. In anotherexample, a user sees a commercial which is fact checked, and the factchecking system indicates the commercial is misleading. The user thensays, “show me a competitor's advertisement,” and a competitor'sadvertisement (e.g., fact checked as valid) is displayed on the user'stelevision or mobile device. In another example, a user is watching anews program which presents one side of an argument, and the user asks,“give me the opposing side's argument.” Then, an opposing argument ispresented to the user. In some embodiments, the opposing argument isbased on the most recent parsed segment in the news program. In someembodiments, a popup screen is presented with choices for a user toselect from to determine which argument he is looking for an opposingargument. In some embodiments, a user specifies the argument he islooking for an opposing argument about. For example, the user says,“give me an opposing argument to the global warming comment.” In someembodiments, after a fact check result is displayed, the user is able tochallenge the fact checking result by saying, “challenge.” In someembodiments, the interactive fact checking system allows a user tospecify individuals or groups to fact check (e.g., “fact checkCommentator X” or “show me a history of fact checks of Commentator X”).In some embodiments, a user is able to request a new fact check withdifferent sources, and the sources are able to be selectedautomatically, manually or a combination thereof as described herein. Insome embodiments, the user is able to request a supporting argument oran opposing argument for specified content. For example, while a user iswatching a political advertisement by Candidate A, the user says, “showme an opposing advertisement by Candidate B,” and then the opposingadvertisement is presented. In some embodiments, a user is able to takea snapshot (e.g., pause) of a screen, then select/highlight what to factcheck or receive supplemental information about. Although the examplesherein focus on voice commands, the interactive fact checking system isable to use any input mechanism such as movement detection and/or anyother input implementation. In some embodiments, the interactive factchecking system operates in real-time. In some embodiments, theinteractive fact checking system recognizes (e.g., face recognition,voice recognition) a user as described herein. Information about therecognized user is able to be used in presenting supplementalinformation or fact checking such as selecting sources to use.

FIG. 51 illustrates a flowchart of a method of implementing aninteractive fact checking system according to some embodiments. In thestep 5100, fact checking and/or searching for supplemental informationis performed as described herein. In the step 5102, a response isreceived from a user. In the step 5104, additional information ispresented based on the response. In some embodiments, the order of thesteps is modified. In some embodiments, more or fewer steps areimplemented.

In some embodiments, a fact check filter is implemented. The fact checkfilter is able to exclude advertisements, articles, stations, channels,programs, events, and/or any other content that has too manyinaccuracies and/or bias (e.g., above a threshold or thresholds). Thecontent is first processed and fact checked as described herein, thenthe filter is implemented to hide or not show content that falls below afilter threshold. In some embodiments, on a channel guide with a tableof show descriptions, shows are highlighted with a designated borderand/or background that have too many inaccuracies and/or bias.

In some embodiments, content (e.g., video) is displayed on a mobiledevice, and fact check results are projected by the device in real-time(e.g., on a wall, table, or any other object) while the content isdisplayed.

In some embodiments, when a factually inaccurate or misleading comment,or other characterization is detected, an icon or tile is displayed onthe screen (e.g., bottom of a mobile device screen or television). Insome embodiments, a list of icons is generated. Users are able to thenselect icons to see additional information. In some embodiments,hovering over or clicking an icon displays the fact checkinginformation. FIG. 52 illustrates a diagram of a smart phone display witha list of icons representing detected characterizations. The smart phone5200 displays a video 5202 or other content which is fact checked usinga fact checking system. When a characterization is detected (e.g.,misleading information, factually inaccurate information, sarcasm, orquestionable information), an icon is displayed corresponding to thecomment. The icons are then able to be presented in a list or otherform. In some embodiments, the icons are presented in the list inchronological order. In some embodiments, the icons are displayed in atimeline, and in some embodiments, a timeline is displayed without iconsto indicate when a fact check result occurred in the content (e.g., afact check occurred at 5:05 in a video with a result of inaccurate, anda fact check occurred at 6:22 with a result of misleading). In someembodiments, the icons are associated with the entity (e.g.,commentator) making a comment. For example, an icon indicates that amisleading comment was made by Commentator A. Indicating who made thecomment is able to be by any implementation such as using a picture, agraphical representation, a symbol, and/or text representing the entity.In some embodiments, the icons are grouped based on the entity (e.g.,all comments by Commentator A are grouped in one group and all commentsby Guest Z are grouped in another group). In some embodiments, the iconsare grouped and displayed in a competitive and/or comparative manner.For example, a head-to-head display ofinaccurate/misleading/questionable/unverified comments ofcommentator/guest is shown, so the viewer is able to see who is makingmore inaccurate comments. In some embodiments, the icons are groupedbased on the characterization (e.g., misleading, inaccurate). In someembodiments, when comments are grouped based on the characterization, anumber appears on or near the icon indicating the number of commentswith that characterization. In some embodiments, when a group containsmore than 1 item, the icon appears to be 3D or multiple icons appear ina layered formation. In some embodiments, when a user selects acharacterization group, the comments are displayed in a list form forthe user to view and/or select for more information. In someembodiments, different sounds, tones, music, vibration schemes, and/orany other output are utilized based on each characterization and/orentity. For example, when misinformation by Commentator A is detected, a“honk” sound is played, and when misinformation by Guest Z is detected,a “beep” sound is played. The exemplary icons shown in FIG. 52 include afactually inaccurate comment icon 5204, a misleading comment icon 5206,a sarcastic comment icon 5208, and a questionable comment icon 5210.Although a smart phone is shown in FIG. 52, the icons are able to bedisplayed on any device (e.g., a television). In some embodiments, theicons are displayed on a smart phone, while the video is displayed onanother device (e.g., television).

In some embodiments, a preemptive fact checking system is implemented.The preemptive fact checking system attempts to anticipate misleading orinaccurate comments and provides factually accurate information beforethe misinformation is presented. The preemptive fact checking system isable to be manually and/or automatically implemented. The information tobe presented preemptively is able to be associated with a person,network, organization and/or any other entity in a data structure. Insome embodiments, a notification is displayed at the beginning of ashow, program and/or any other event, to alert people to keep an item inmind while watching the program. The beginning of the show is detectedin any manner (e.g., by time, audio recognition, video recognition), andbullet points of facts generated automatically and/or manually based onrecent/current news/stories are displayed on a television, a mobiledevice and/or another device. For example, a report showing unemploymentwent down is released, and included in the report is the number thatindicates it went down because many people stopped looking for work. Toprevent the misrepresentation of the seemingly positive unemploymentnumber, an alert is presented that informs the user at the beginning ofa news program that unemployment went down because of X number of peoplestopped looking for work.

In some embodiments, the fact checking system determines whether arespondent answers a question. The fact checking system analyzes thequestion asked, and then based on the response, determines whether thequestion was answered. Determining if the question is answered is ableto be performed in any manner, for example, locating and/or storing aset of appropriate responses, comparing the response with theappropriate responses, and if the response is similar, then the questionhas been answered properly. Another example of determining if thequestion is answered is by comparing the number of relevant words to thequestion and determining if the number of relevant words is above athreshold. For example, if the question is about the economy, and theanswer only mentions one word related to the economy, then the responseis deemed to be unresponsive. The related words are able to be stored ina data structure used for comparison purposes. The fact checking systemindicates in real-time a responsiveness response such as “evading” or“didn't answer the question” or “didn't answer the question fully,” orsimilar language, and/or provides a number rating of responsiveness 0(did not answer at all) to 10 (fully answered). Other indications areable to be used to describe the responsiveness of an answer. In someembodiments, users are able to flag a response as unresponsive (e.g.,voice command “unresponsive”). In some embodiments, a flagged response(by enough users) is checked for responsiveness. In some embodiments, ifenough users flag a response as unresponsive, the response andresponsiveness are documented in a data structure for the entity (e.g.,a guest on a show).

FIG. 53 illustrates a flowchart of a method of determining if arespondent answers a question according to some embodiments. In the step5300, the question is monitored and processed (e.g., parsed). In thestep 5302, the answer is monitored and processed (e.g., parsed). In thestep 5304, the processed question and answer are compared with sourceinformation (e.g., database information) to determine if the questionwas answered appropriately. In the step 5306, a result of whether theanswer was appropriate is indicated. In some embodiments, the order ofthe steps is modified. In some embodiments, more or fewer steps areimplemented.

In some embodiments, a commentator refers to a source, and the factchecking system determines the reliability and/or bias of the source andindicates the reliability/bias of the source.

In some embodiments, fact checking results are able to be swiped,bumped, uploaded, or moved from one device or window to another deviceor window. In some embodiments, the move causes an auto-correction ofthe information on the second device. For example, a user's name is factchecked, and the correct spelling is located on a first device. Then,the information is swiped using a user's finger and directed at a seconddevice with the incorrect information. The information is then correctedafter the swipe by locating the misinformation and replacing it with thecorrect information. In some embodiments, a user is able to swipe, bump,upload or move documents, videos, and/or other content to a televisionor other fact checking device to be fact checked. For example, a user iswatching a video on his mobile device, and he swipes the video to astand-alone fact checking device, which fact checks the video, andreturns a result to the mobile device for presentation. In someembodiments, a device detects nearby devices and automaticallydetermines which device is best to display certain content. For example,a user is watching a program on a television. The program is factchecked, and the television determines that the fact check resultsshould be sent to and displayed on the user's smart phone. The automaticdetermination is able to occur based on the size of the content (e.g.,display large graphics on television instead of smart phone screen),based on the type of the content, and/or based on any other aspect ofthe content or the devices. In some embodiments, the user is able tospecify which type of content is displayed on which device. For example,a user decides he does not want fact check information displayed on thetelevision, and the user specifies through the television, the mobiledevice, or in the cloud, that he wants the fact checking results to bedisplayed on his mobile device.

In some embodiments, supplemental information is specifically providedfor turning content generally directed at adults into contentappropriate for children. For example, if a mother is watching aPresidential debate on a television, and her child is watching along,supplemental information explaining the content and/or other aspects ofthe debate or government are presented on the television or a seconddevice (e.g., smart phone or tablet). Furthering the example, thesupplemental information could include how long a president is inoffice, requirements to become president, how the electoral collegeworks, and/or specific explanations of the debate. For example, if acandidate discusses economic policies, cartoons and/or simplifiedinformation is able to be presented related to the economic policies.The child-specific information is able to be stored in a data structureand retrieved and displayed when a keyword is detected or based ontiming of the event. For example, if the word “economy” is detected,graphics about money are displayed. In another example, at the 5 minutemark of the debate, additional information about the presidency isdisplayed such as historical data. In some embodiments, the supplementalinformation includes games and/or quizzes related to the subject matter.The child-specific information is able to include fact checking resultsas well and provide lessons to learn based on the fact checking. In someembodiments, the mature content is converted into a cartoon or animatedprogram.

FIG. 54 illustrates a flowchart of a method of providing contentappropriate for children based on content directed at adults accordingto some embodiments. In the step 5400, information is monitored (e.g.,broadcast information). In the step 5402, the content is detected asdirected to mature material. The content is able to be detected asmature by comparing keywords in the content with a database, based on atitle of the content, based on a subject of the content, based on alookup table of what content is on and when, where the content isalready classified, based on a user selection indicating maturematerial, and/or in any other manner. In the step 5404, child-specificcontent is located (e.g., searching a database for presidential debateand locating a supplemental video which explains three branches ofgovernment or a quiz about the Presidents). In the step 5406, thechild-specific content is presented. For example, the child-specificcontent is presented on a mobile device (e.g., tablet computer) whilethe television shows the mature content. In some embodiments, the orderof the steps is modified. In some embodiments, more or fewer steps areimplemented.

In some embodiments, comments (or segments of comments), and/or otherinformation is classified by political party or another political/socialclassification. For example, a commentator says, “the government shouldstay out of the free market, but the people own the land so thegovernment should control the price of oil and gasoline.” The first partof the comment (before the “but”) could be classified as libertarian,conservative, republican, and/or a similar classification. The secondpart of the comment (after the “but”) could be classified as socialistor another similar classification. In some embodiments, theclassifications are presented (e.g., indicated in real-time on a user'sscreen). In some embodiments, the classifications are stored along witha tally of the number of comments in each classification, and the tally(e.g., in a chart, statistics) is presented during the event/show, atthe end of a segment of an event/show, at the end of an event/show orpresented at another time (e.g., when a commentator or other entity isdetected). For example, at the end of a show, a tally indicates that thehost of the show made 35 conservative comments and 5 liberal comments.In some embodiments, a comparative chart is presented comparing thecomments of the host, guests, and/or other entities. The comments areclassified in any manner, for example, comparing the comments with adatabase of classified comments, and a comment is classified based onits closest classified comment. In some embodiments, the comments areclassified automatically, classified automatically and verifiedmanually, or classified manually by a human.

FIG. 55 illustrates a flowchart of a method of classifying informationby political party/view according to some embodiments. In the step 5500,information is monitored (e.g., broadcast information) as describedherein. In the step 5502, the information is processed as describedherein. In the step 5504, the information is classified by comparingkeywords or key phrases with a data source (e.g., online sites and/or adatabase) to determine which political classification the comments isnearest to. In an example, if the comment is similar to or the same as acomment by an Internet blogger that is conservative, the comment is ableto be classified as conservative. The source of the source is able to beone factor in determining the classification. For example, although thecomment is similar to a conservative blogger, if the comment is similarto a previously classified comment that is classified as socialist,then, in some embodiments, the previous classification is given moreweight, and the comment is classified as socialist. In the step 5506,the classification is indicated as described herein. In someembodiments, the order of the steps is modified. In some embodiments,more or fewer steps are implemented.

In some embodiments, “loaded” words/questions/information (e.g.,terms/phrases meant to cause strong positive or negative responses, havenegative or positive connotations, or are emotive) are monitored for,detected, and highlighted. For example, if a commentator says, “electingcandidate Z is dangerous,” then “dangerous” is highlighted for the user.In some embodiments, a positive/negative connotation is also indicatedby the loaded word. In some embodiments, the way of highlighting isbased on the strength of the word (e.g., a word that is highly emotiveis significantly highlighted, where a word that is only slightly emotiveis lightly highlighted). In some embodiments, additional information isprovided to indicate that the language being used is biased (in one wayor another). Furthering the example, referring to a candidate as“dangerous” indicates bias against that candidate by the commentator.Loaded words and tallying the number of times loaded words are used areable to be used in determining bias. For example, if a commentatorrefers to a candidate with 5 words that have a negative connotation and0 words that have a positive connotation, it is able to be deduced thatthe commentator has a bias against the candidate. In some embodiments,the relationship of the loaded words to the subject (e.g., candidate) isanalyzed and used in determining bias. For example, words that aredirected towards the subject are given more weight than words that aremerely mentioned while talking about the subject. For example,“candidate Z is dangerous” is given more weight than “candidate Ztraveled to Afghanistan which is dangerous.” Other contextual featuresare able to be analyzed and utilized in determining whether loaded wordsindicate bias. In some embodiments, only loaded information/comments arefact checked as described herein. For example, when a commentator in amonologue discussing candidate Z states that “candidate Z is dangerous,”the sentence segment involving the loaded word “dangerous” is factchecked and/or supplemental information is searched for. For example,supplemental information indicating why candidate Z might be dangerousor fact checking information that disagrees with the comment isindicated based on a source information search. In some embodiments,weight of the loaded words depends on where or when the words are used.For example, if the loaded words are used in a title of an article or atthe beginning of a monologue, they are given more weight than if theyare in the middle of an article. The weight could be used as anotherfactor in determining bias. For example, if the weighted number ofloaded words with a negative connotation is above a threshold, it isdetermined that a bias exists between the commentator and the subject.In some embodiments, loaded words, who said/wrote them, who they areabout, and/or other information are stored and used for comparisonpurposes.

FIG. 56 illustrates a flowchart of a method of detecting andhighlighting loaded words according to some embodiments. In the step5600, information is monitored (e.g., broadcast information) asdescribed herein. In the step 5602, the information is processed asdescribed herein. In the step 5604, loaded words are detected within theprocessed information. The loaded words are able to be detected bycomparing the processed information with a data source (e.g., onlinesites or a database). For example, a database stores all loaded wordsand phrases, including negative/positive connotation, and when a loadedword/phrase is found in the database, the loaded word is indicated(e.g., highlighted) in real-time on the screen in the step 5606, asdescribed herein. In some embodiments, the order of the steps ismodified. In some embodiments, more or fewer steps are implemented.

In some embodiments, specific keywords and/or characters are detectedfor determining whether to fact check a search engine input. Forexample, when a user includes a question mark at the end of the searchstring input in a search engine, the search engine fact checks thesearch string instead of simply searching for pages related to thesearch string. Any keywords or characters are able to be used, and anylocation of the keywords is able to be used. For example, when a usertypes “fc”+search string+“?” then the search fact checks the searchstring. The detectable fact check keywords/characters are able to bestored in a database, and each search engine input is parsed andcompared with the stored keywords/characters. Any other implementationis able to be used to determine if the search string is to be factchecked. After the fact check keywords/characters are detected, thesearch string is compared with source information as described herein. Aresult of the fact check is then indicated as described herein.

In some embodiments, accusations of bias by a first entity against asecond entity are detected. For example, if Network A accuses Network Bof being biased for not discussing Story X, then references of Story Xin Network B are searched for and/or monitored for and indicated.Furthering the example, Network A says Network B is not covering StoryX, and a search of Network B data (e.g., archives) is performed, and ifthere are no matches or “hits,” then either no additional information ispresented or a message such as “this accusation is correct” is presentedin real-time. However, if there are matches, then an indication ispresented in real-time such as, “this accusation is incorrect.”Additional information is able to be provided such as the number oftimes Story X was discussed, the ratings during Story X showing that itis unpopular and thus why not discussed more, fact checking informationindicates the story is not accurate (e.g., story is fact checked, andresult is that the story is not accurate or not verified), links tovideos, articles and/or other information discussing Story X by NetworkB, and/or any other supplemental described herein. Detecting biasaccusations is able to include monitoring information as describedherein, detecting an accusation of bias by an entity (e.g., notreporting, underreporting, over reporting a story, event or anyinformation), searching for and/or monitoring for the accusedinformation on the accused entity or entities, and indicating the resultof the searching/monitoring in real-time. In some embodiments, the biasaccusation information is not presented on an initial detection of theaccusation, but subsequent presentations of the accusation areaccompanied by the results of the bias accusation search. For example, acommentator on Network A claims Network B is not covering Story X. It isdetermined in real-time or non-real-time if Network B is covering StoryX. If Network B is covering Story X, the next time the commentator oranother commentator on Network A or another entity (e.g., blogger) isdetected and/or claims Network B is not covering Story X, thesupplemental information showing that Network B is covering Story X ispresented with the comment proving the comment to be false. The nexttime is able to include during a rebroadcast/rerun, during apresentation of the information on the Internet, radio and/or othersystem, when another entity makes the same or similar claim, and/or anyother time.

FIG. 57 illustrates a flowchart of a method of detecting accusations ofbias by one entity against another according to some embodiments. In thestep 5700, an accusation is detected. Detecting the accusation is ableto be performed in any manner. For example, information is monitored fora keyword or phrase indicating an accusation (e.g., words/phrases thatindicate an accusation are stored in a database for comparison—“NetworkB ignores”). In the step 5702, an interest level is determined. Forexample, ratings statistics are analyzed about the popularity of atopic/story/any other information. In the step 5704, if the interestlevel is above a threshold, then the accused entity and/or relatedentities are analyzed (e.g., archives of past reporting are searched forthe accusation). In the step 5706, if the interest level is not abovethe threshold, then it is indicated that the information is below aninterest level. In the step 5708, a result of the analysis of theaccused entity is presented. For example, the result is displayed on auser's television and/or mobile device at the bottom of the screen. Insome embodiments, the order of the steps is modified. In someembodiments, more or fewer steps are implemented. For example, the stepsinvolving the interest level are skipped, and factual accuracy of theaccusation is checked regardless of the interest level.

In some embodiments, a search engine utilizes social network informationand fact checking information to perform a search. In some embodiments,a search engine manages a search results database and another databaseis a user database that keeps track of all search queries specified byeach user and for each search query, a record of all links the userclicked when search results based on the search query were presented tothe user. In some embodiments, the links are or have been fact checkedwhich affects their ranking/ordering as described herein.

In some embodiments, the search engine utilizing social networkinginformation and fact checking information to perform a search, performsa search, the search results are fact checked, the fact checked searchresults are compared with social network information, and search resultsare displayed based on the search, fact check and the social networkcomparison.

FIG. 58 illustrates a flowchart of a method of using a search engine incooperation with social network information and fact checkinginformation according to some embodiments. In the step 5800, a searchengine retrieves search results responsive to the search query from asearch results database. In some embodiments, the search results includefact checked information (e.g., web pages). In the step 5802, factchecking is applied to the search results. In some embodiments, thesearch results are retrieved and then fact checked as described herein.In the step 5804, the search engine searches a database (e.g., a thirdparty database) for search queries that match the one received from theuser. If there are no matches, the search results retrieved in the step5800 are presented to the user in the step 5806. If there are one ormore matches, the search results are ranked based on a scheme such asthe frequency of “relevant” clicks on the links associated with thesearch results and then presented to the user in the step 5808.Frequency of clicks is equal to the number of prior clicks on a linkdivided by the number of times that link was displayed, and links withhigher frequencies are ranked higher than links with lower frequencies.In some embodiments, a combination of frequency and factual accuracy iscomputed, and links with a higher combined score are ranked higher thanlinks with a lower combined score. Relevant clicks are clicks made byusers who are within a specified degree of separation from the user whorequested the search. The degree of separation information (e.g., socialnetwork or relationship information) is able to be maintained by thesearch engine or obtained from an online social network. The specifieddegree of separation is able to be any number or set as ALL, in whichcase all clicks become relevant, and it is able to be set by theoperator of the search engine, or it is able to be set by a user in hisprofile. For example, if the user sets the specified degree ofseparation as 1, only clicks made by those who are friends of the userbecome relevant clicks. When the system receives an Internet searchquery from an Internet user who is not a member of the online socialnetwork, it retrieves the search results responsive to the search queryfrom the Internet search results database, and searches the Internetsearch query database for search queries that match the one receivedfrom the user. If there are no matches, the search results retrievedfrom the Internet search results database are served to the user. Ifthere are one or more matches, the search results retrieved from theInternet search results database are ranked based on the frequency ofclicks on the links associated with the search results and then servedto the user. In some embodiments, the order of the steps is modified. Insome embodiments, more or fewer steps are implemented.

In some embodiments, social networking information is used for contextdetermination. For example, social networking information is able toprovide political context (e.g., person is a conservative based on“liked” blogs or contacts), economic context (e.g., person'sincome/wealth is in the top 5% based on the trips taken described on asocial network site), time/date context, location context, socialcontext, legal context, and/or any other context. Determining thecontext is able to be performed in any manner (manually, automaticallyor semi-automatically) such as by searching for keywords or phrasesand/or classifying information contained within the social networksites.

In some embodiments, a message board fact checking system forautomatically fact checking message board postings is implemented. Avalidity rating as described herein is used for usernames (e.g., postednext to or near usernames). A validity rating for a username is modified(e.g., increased or decreased) based on the factual accuracy of thepostings using the username. For example, Username A has a −5 validityrating for 5 factually inaccurate postings. In some embodiments, eachfactually inaccurate comment affects the rating (potentially many in asingle posting), and in some embodiments, a posting is considered intotal (e.g., 5 inaccuracies in 1 posting only counts once against theuser). In some embodiments, factually inaccurate content is highlighted(e.g., in red) for the user so that he is able to correct his postand/or for everyone to be alerted to the misinformation. Postings and/orcontent within each posting are able to be classified and/orcharacterized using any of the classifications/characterizationsdescribed herein such as political classifications, hyperbole, sarcasm,inaccurate, bias, and/or comedy. In some embodiments, users are able toincrease their validity rating by posting factually accurateinformation, flagging other postings (including providing sources),and/or correcting other postings. In some embodiments, flagged postingsare able to be fact checked by the user, others, and/or automatically bythe fact checking system. Users are able to submit a source supportingthe flag (e.g., comment X is inaccurate based on cite Z). In someembodiments, the validity rating for a message board includes factuallyinaccurate comments and the number of corrections displayed separately.In some embodiments, a user is not permitted to post if his validityrating falls or is below a threshold. When a user is not permitted topost due to a low validity rating, the user is able to raise hisvalidity rating by flagging factually inaccurate postings, fact checkingpostings, characterizing postings (e.g., identifying correctly a postingto be hyperbole), and/or in other ways, so that eventually the user'svalidity rating is above the threshold. To prevent users from avoidingthe validity rating system, validity ratings are able to continue with auser even if a user changes his username. Username changes are able tobe determined by comparing IP address, language of posts and/or otherinformation to prevent users from changing names after posting factuallyinaccurate information. Items/statistics (e.g., inaccuracies, postinginaccurate sources, bad language) about a user are able to be stored,sorted, searched and/or posted. In some embodiments, when a user posts acomment on a message board, the comment is fact checked before beingposted for public view, and if the comment is not verified as factuallyaccurate, the user is prompted to provide a reason, justification,and/or citation supporting the comment. For example, a user attempts topost, “the president is a Communist.” The message is fact checked inreal-time and determined to be factually inaccurate. The user is thenrequested to provide a reason or citation justifying the message. Insome embodiments, if the reason or citation supports the message (e.g.,the reason or citation is fact checked by the fact checking system andfound to support the message), the message is posted for public viewing,and if the reason or citation does not support the message, the messageis rejected and not posted. In some embodiments, the citation isverified by the fact checking system (e.g., the fact checking systemdetermines the reliability of the source). In some embodiments, areliability rating of the source is provided when the message is posted.In some embodiments, the message is not further verified, but the reasonand/or citation is posted with the message. In some embodiments, theuser is prompted to select a classification (e.g., fact, opinion,hyperbole, sarcasm). In some embodiments, message board posts are ableto be sorted based on factual accuracy and/or other criteria such asmost liked/popular, newest/oldest, most controversial, and/or others. Insome embodiments, the validity rating is able to be used at multiplemessage boards. For example, if a user has the same username, the samevalidity rating is displayed at different message boards. In someembodiments, even with a different username, the system is able todetermine the same user (e.g., based on IP address) and maintain thesame validity rating. In some embodiments, if a posting is factuallyinaccurate (e.g., more factual inaccuracies than a threshold or a higherpercentage of factually inaccurate comments than factually accuratecomments), then the posting is hidden or not shown.

FIG. 59 illustrates a flowchart of a method of fact checking a messageboard according to some embodiments. In the step 5900, message boardpostings are fact checked automatically. Fact checking the message boardpostings includes processing the postings, fact checking the postings,and indicating fact checking results (e.g., highlighting parts of aposting or a whole posting based on the fact checking). In the step5902, users are provided with a validity rating based on the factchecking. In some embodiments, the order of the steps is modified. Insome embodiments, more or fewer steps are implemented.

FIG. 60 illustrates a block diagram of fact checking interactions with amessage board according to some embodiments. The interactions with themessage board fact checking system include, but are not limited to,flagging 6000 content and/or postings on the message board, correcting6002 content/postings, fact checking 6006 a comment before publishingthe comment, and/or classifying 6004 of content/postings.

FIG. 61 illustrates a screen shot of an exemplary message boardimplementing fact checking according to some embodiments. The messageboard includes validity ratings 6100 for each user. For example, Bob hasa +5 validity rating for flagging inaccurate postings and not postinginaccurate comments; Jay123 has a −3 validity rating for postinginaccurate comments; and Con has a −1 validity rating for posting atleast one inaccurate comment. The validity rating is also able toindicate bias based on determining bias as described herein andindicating (“liberal,” “conservative,” “moderate,” and/or any other biascharacterization). The message board includes highlighting 6102 ofcomments that have been fact checked and determined to be factuallyinaccurate.

FIG. 62 illustrates a screen shot of an exemplary message boardimplementing fact checking before allowing a user to post according tosome embodiments. In the screen shot 6200, a user attempts to submit apost. In the screen shot 6202, the user is informed that a fact checkhas been performed, and the user is asked to provide support for thecomment. In the screen shot 6204, the user provides a link supportingthe comment. In the screen shot 6206, after the comment and the linkhave been analyzed (e.g., fact checked/checked the reliability), amessage to the user indicating that the message is posted with anaddition of a reliability rating for the source. Although in thisexample, a reliability rating of the source is posted, in someembodiments, the reliability rating is not posted, or if the reliabilityrating of the source is below a threshold, the user's post is rejected,or another action is taken.

In some embodiments, advertising posting sites, auction sites, and/orsales sites (e.g., Craigslist, eBay®) are fact checked automatically.Specific advertisements are able to be fact checked, and advertisementsare able to be associated with a user. The user is able to have avalidity rating as described herein. If a user's validity rating fallsor is below a threshold, the user is not permitted to post anadvertisement, or the advertisement is highlighted in some manner asbeing posted by an untrustworthy user. The validity rating based on factchecking is able to be combined with seller/buyer ratings (e.g., ratingsby purchasers or sellers about sellers or purchasers) to provide acombined rating of a user. The user's validity rating is able to bespecific to a site or based on multiple sites.

In some embodiments, polls are tracked for future comparison. Forexample, in an election year, many different entities perform polling toproject how an election will turn out. The polling from the differententities is able to be tracked and stored by the fact checking systemand compared with the actual results of the election. Then, the resultsof the comparison are able to be stored and presented in futureelections. For example, in 2012, the final poll of Poll X indicates thatCandidate A is winning in Ohio by 5%. In the actual voting, Candidate Bwins Ohio by 3%. The information is stored in a data structure. Then, in2016, when Poll X or a reference to Poll X is detected (e.g., bymonitoring), information about how Poll X was wrong in 2012 isautomatically indicated as described herein. Additional information isable to be stored, such as a count of correct and incorrect polling. Forexample, Poll X performs polls in all 50 states and is correct in 48states which is stored. Later, supplemental information such as Poll Xhad 96% accuracy in 2012 is able to be displayed. Additionalsupplemental information is able to be presented as well such as whyresults were incorrect (e.g., oversampling of a demographic) and/orcomparison data with other polls (e.g., Poll X was correct 96% of thetime, Poll Y 90%, and Poll Z 80%).

In some embodiments, a debate fact checking system is implemented. Thedebate fact checking system is implemented similarly to the factchecking system by monitoring information, processing the information,fact checking the information, and indicating results. Indicatingresults is able to include keeping a tally of misleading comments,inaccurate comments, and/or any other characterizations. In someembodiments, a winner of the debate is determined by the tally ofcharacterizations. For example, Candidate A is determined to have made 5inaccurate comments, and Candidate B is determined to have made 15inaccurate comments, so Candidate A is declared the winner. In anotherexample, a participant is awarded a point for correcting an opponent'sinaccurate or misleading comment, and a point is taken away when aparticipant makes an inaccurate or misleading comment. In someembodiments, a participant is awarded a point for making an accuratecomment.

In some embodiments, in a tablet that doubles as a laptop (e.g., atablet with two screens or displays), the fact check results and/orsupplemental information is displayed on the second screen while themonitored content is displayed on a first screen.

In some embodiments, the fact checking system automaticallysends/receives contradictory information from an opposing point of view.For example, a user is a Republican, and a conservative commentatorpoints to negative information about a Democrat. Video clipscontradictory to the commentator's points are presented to the userbased on the user's party affiliation (Republican, in the example).

In some embodiments, controversial topics and arguments for either sideof the topic are tracked. For example, climate change is a controversialtopic to many people. Although a large amount of science supports thetheory of climate change, many people continue to be skeptical, partlybecause bogus arguments are used to attack the theory of climate change.A database including the accuracy of each argument is able to begenerated and maintained. Additionally, in some embodiments, expertsfrom each side of an argument are able to contribute to the databaseincluding providing support for each argument. In some embodiments, thetopics and the arguments are automatically monitored, the factualaccuracy of the argument is automatically determined by comparing thearguments with source information, and a result is returned. In someembodiments, after the arguments are analyzed automatically, the resultis manually verified by a user and/or an expert.

In some embodiments, fact checking information (e.g., results andsupplemental information) is displayed in a similar manner to pop-upadvertisements embedded in video (e.g., YouTube® in-video ads). Forexample, every time a fact check result is to be displayed, a bar orother marker is indicated on a time scroll bar. And every time the videopasses the fact check bar, an in-video fact check result and/orsupplemental information (e.g., pointing out bias, an opposing argument)is displayed. In some embodiments, the in-video fact check result orsupplemental information is able to be based on a previous fact check.The previous fact check is able to be performed automatically, manually,or automatically with a manual verification. In some embodiments, thefact checking system generates embedded fact checking pop-ups while factchecking. For example, while a video is monitored and fact checked, if acharacterization (e.g., factually inaccurate, misleading) is detected,an in-video fact check result is embedded in the video. Each fact checkresult occurrence is embedded in the video, so that any subsequent viewsof the video, the embedded fact check result is available. When a userviews the video, at each designated time, the embedded fact check resultwill pop up or otherwise be displayed.

In some embodiments, a fact check result is displayed in a preview,thumbnail, television guide display, and/or any other preliminarycontent. For example, a thumbnail of a video for a political debateincludes text of an incorrect statement and an indication such as“false” and/or a correction. In some embodiments, the text is embeddedwithin or overlaid on the thumbnail. In some embodiments, only the mostsignificant fact check result or most important to the user or ingeneral is displayed. In some embodiments, a list of fact check resultsare displayed. In some embodiments, fact check statistics are displayedin the thumbnail. In some embodiments, statistics are displayed in acomparative format (e.g., in a table or chart).

In some embodiments, common factually inaccurate arguments are storedincluding responses to the inaccurate arguments. When a factuallyinaccurate argument is detected and/or searched for, a response or alist for responses is presented to a user. For example, a smart phonemonitors a user's conversation, processes the conversation as describedherein, and detects a factually inaccurate argument (e.g., by anotherperson). Upon detection, a single response or list of responses to theinaccurate argument are automatically presented on the smart phone. Theresponses are able to be generated in any manner such as automatically,automatically and verified manually, or manually. In some embodiments,only the most common and/or recent factually inaccurate arguments arestored. In some embodiments, the factually inaccurate arguments arestored, sorted and/or searched through based on commonness (orpopularity), timeliness (e.g., recent versus many years ago), and/orrelevance to a user and/or topic. For example, a commonmisrepresentation of information is stored at the front of a list, sothat it is analyzed first when searching for a factually inaccurateargument.

In some embodiments, product reviews are fact checked. For example,users are able to review products they purchase on web sites such asAmazon.com. In the reviews, users are able to input any review of theproduct without much if any oversight by the selling web site. Theproduct review fact checking system is able to be implemented toautomatically monitor product reviews (e.g., using a crawler/bot), orincluding a button or link on a page for a user to click to initiate afact check of a review or reviews. For example, each review is able tohave a mechanism for a user to trigger a fact check of the review. Thefact check of the review is able to be implemented in any manner. Forexample, the review analyzes other reviews to determine if there is acommon issue with a product. Furthering the example, a fact check of“battery life is too short” determines that 10 other reviews include thesame or a similar complaint. The fact check result is able to present aresult such as “10 reviews support this point.” If reviews are foundthat disagree with a point; for example, 10 reviews say, “great batterylife,” then the result is able to indicate, “10 reviews disagree withthis point.” In some embodiments, the supporting and/or disagreeingreviews or links thereto are presented. In some embodiments, factchecking a product review includes confirming the user actuallypurchased the item. For example, the username for review iscross-checked with a database of purchases by that user. Other sourcesare able to be used to verify a user actually purchased an item such associal network information. In some embodiments, when a user posts anissue in a product review, the issue is verified as being possible withthe item. For example, a user complains that the lights do not work on atoy, yet the toy does not include any functioning lights, the issue isflagged such as “not possible” or “errant.” In some embodiments, theproduct review fact checking system reports and/or confirms issues withthe manufacturer, seller, and/or other entity. For example, themanufacturer is able to confirm or deny that a certain part issusceptible to breakage. In some embodiments, the fact checking resultsare sent to the manufacturer.

FIG. 63 illustrates a flowchart of a method of fact checking productreviews according to some embodiments. In the step 6300, product reviewsare monitored. In the step 6302, the product reviews are processed(e.g., parsed). In the step 6304, the product reviews are fact checked.In the step 6306, the fact check result of the product review isindicated. In some embodiments, the order of the steps is modified. Insome embodiments, more or fewer steps are implemented.

In some embodiments, the fact checking system monitors for criticism ofbias or inaccuracy of the fact checking system by others, and whenfound, the source (e.g., a network, a commentator, a website, and/or anyother entity) of the criticism is monitored to correct in real-time anymisrepresentations of the fact checking system. In some embodiments,when the source of the criticism is detected making a comment about thefact checking system, fact checking system statistics and/or comparativedata is presented automatically as described herein. In someembodiments, after a source is determined, any future detection of thatsource automatically triggers a display of fact checking systemstatistics and/or comparative data. For example, the fact checkingsystem monitors broadcast information and determines that Commentator Xsaid, “this new fact checking system distorts the truth.” The factchecking system stores Commentator X's information (e.g., name, show,network), and then specifically monitors Commentator X in general andfor specific comments about the fact checking system. When Commentator Xis detected again or when a comment by Commentator X about the factchecking system is detected again, information rebutting Commentator Xis indicated (e.g., Here are all of the fact checking results andsources or Here is a table comparing the factual inaccuracies spread bythe fact checking system versus Commentator X). In some embodiments, anautomatic rebuttal to the initial criticism is automatically presentedincluding, but not limited to, accuracy statistics of the fact checkingsystem and/or the critic/critic's organization, a link to the factchecking system home page, specific information/sources disproving thecriticism, and/or additional information. In another example, whencriticism is detected, rebuttal information of the criticism isdisplayed for a designated time period (e.g., the next five days) whenthe commentator, show, network, affiliates, and/or another entity aredetected. In some embodiments, a response to criticism includes areference to a source that is from the same classification (e.g.,political classification) as the commentator. For example, aconservative commentator criticizes the fact checking system as beingbiased for indicating a Republican candidate's speech as factuallyinaccurate. The fact checking system displays evidence including acitation from a Republican source that the fact checking system wasaccurate in its characterization of the speech. In some embodiments, anetwork and/or associated entities are monitored, and statistics and/orcomparative data is displayed. For example, a host on Network Z unfairlycriticizes the fact checking system. When an associated website ofNetwork Z (e.g., determined in a relational database) is detected, thestatistics/comparative data is displayed. In some embodiments, whencriticism of the fact checking system is detected, the criticism isanalyzed for taking the fact check information out of context, and inresponse, context is provided by the fact checking system. In someembodiments, if the criticizing commentator points to a result by thefact checking system as wrong, but the result has been corrected by thefact checking system, the fact checking system is able to indicate thatthe commentator is using old data, and the fact checking system hasupdated its result, and the updated result is presented. In someembodiments, if a critic presents statistics about the fact checkingsystem that are not correct, the fact checking system provides correctstatistics including a source or sources of the correct statistics. Insome embodiments, a user is able to flag comments, commentators,networks and/or other information or entities that criticize the factchecking system. The fact checking system is then able to perform asdescribed herein to rebut the criticism and/or monitor for additionalcriticism. In some embodiments, the response to the criticism isdisplayed on a second device (e.g., criticism is displayed on atelevision, and response is displayed on a smart phone).

FIG. 64 illustrates a flowchart of a method of monitoring for criticismof the fact checking system according to some embodiments. In the step6400, information (e.g., broadcast) is monitored for criticism of thefact checking system. In the step 6402, criticism is detected. In thestep 6404, information in response to the criticism is presented. Insome embodiments, the order of the steps is modified. In someembodiments, more or fewer steps are implemented.

In some embodiments, the fact checking system alerts users who areinterested in fact checking but are not aware that the fact checkingsystem exists. For example, a device detects that a user is interestedin news programming, and it is also determined that the user does nothave a fact checking app or fact checking television, so a notificationis presented to the user of the fact checking system, and a way (e.g., alink) for obtaining the fact checking system is provided.

In some embodiments, a device (e.g., a smart phone) detects that a userwatches or listens to factually inaccurate content, and presents (e.g.,pops up) advertisements to download/obtain the fact checking system.

In some embodiments, basic/simple videos and/or other information isprovided to help people understand a complex point such as the nationaldebt/deficit.

In some embodiments, a runny tally or clock of the amount of time (ornumber of times) discussing/showing each candidate, topic, entity,and/or other information on a show, a website, a channel, a set ofchannels, or a group of information distributors (e.g., conservativenews channels, radio and web sites or liberal media channels, groups,web sites) is determined, collected and displayed. In some embodiments,the analysis includes determining if the candidate/topic is discussedpositively, negatively, or neutrally. For example, in a simple version,it is determined that Channel X discusses Candidate A for 500 minutesand Candidate B for 550 minutes in October. In a more complex version,it is determined that 450 minutes of the discussion about Candidate A isnegative and 50 minutes is neutral, and 520 minutes of the discussionabout Candidate B is positive and 30 minutes is neutral. Determining theamount of time or the number of times a candidate, entity, topic and/orother information is discussed, and whether the discussion is positive,negative, or neutral is able to be performed in any manner including,but not limited to, detecting keywords in a title of a segment of ashow, detecting keywords throughout the segment of a show, detecting byfacial or voice recognition as described herein, detecting loaded wordsas described herein, detecting bias as described herein, based on userflagging (e.g. users flag start/end times of a story as being aboutand/or involving Candidate A and whether the story is positive,negative, or neutral), based on fact checking, and/or any other manner.In some embodiments, the amount of time and/or number of times anentity/topic is discussed is able to be used in determining bias. Forexample, if a network discusses a first candidate positivelysignificantly more often than an opposing candidate, biased for thefirst candidate is able to be determined. In some embodiments, theanalysis is performed automatically, automatically and verifiedmanually, or manually.

FIG. 65 illustrates a flowchart of a method of calculating the amount oftime or number of times an entity or topic is discussed according tosome embodiments. In the step 6500, an entity/information is detected.In the step 6502, an amount of time the entity/information is detectedis computed. In the step 6504, the amount of time is presented (e.g.,displayed on a television automatically when a user watches a specifiedchannel). In some embodiments, the order of the steps is modified. Insome embodiments, more or fewer steps are implemented.

In some embodiments, fact checking is implemented selectively. Forexample, information (e.g., broadcast information) is monitored andprocessed, but fact checking only occurs when specific words or phrases(also referred to as triggers) are detected or when a specific entity(e.g., commentator) is detected. In some embodiments, triggers for theselective fact checking include, but are not limited to, a specificevent (e.g., “Iraq War”), a specificnetwork/channel/show/commentator/guest (e.g., network XYZ), a specifictopic (e.g., “taxes”), a specific characterization (e.g., “liberal”), arecent news story (e.g., “fiscal cliff”), an item related to a user'simportance as described herein (e.g., “jobs” or related words), anentity with a validity rating below a threshold (e.g., Guest X has avalidity rating of −10), popular items (based on trending information),time relevance (e.g., story is about recent events), recent purchases bythe user (e.g., user just purchased a Make/Model X car), recent searchesby the user (e.g., search inputs to search engines), social networkinformation, personal information of the user, political affiliation ofthe user, a controversy, a controversial comment, a hashtag, and/or anyother trigger. For example, the system monitors for comments about aspecific event such as “Iraq War,” and when the phrase is detected, factchecking occurs. The words/phrases/entities to be detected are able tobe stored in a data structure or searched for in another manner, andwhen a match is detected, the entity, phrase, word, or phrase the wordis in is detected. In some embodiments, users are able to specify thewords/phrases/entities to be detected. In some embodiments, usersspecify words/phrases/entities to be detected by flagging (e.g., voicecommand to a television to flag a word). The selectivity is able to beimplemented in any manner, for example, separating content into opinionand facts, and only fact checking facts. In another example, the contentis separated into opinion and facts, and the opinion is analyzed forbias, and the facts are fact checked. In another example, fact checkingonly occurs when a political word or phrase is detected, and surroundinginformation is fact checked (e.g., the phrase the word is in or severalseconds before and/or after the word is detected). In some embodiments,detecting a word triggers fact checking a segment of a show (e.g., untila commercial break), a web page, or another subset of information. Forexample, a web page is analyzed, and if the web page does not containany trigger words, the web page is not fact checked. In someembodiments, a web page, show, and/or other content is fact checked onlyif the number of trigger words exceeds a threshold.

FIG. 66 illustrates a flowchart of a method of implementing selectivefact checking according to some embodiments. In the step 6600,information is monitored. In the step 6602, the information isprocessed. In the step 6604, a word/phrase/entity is detected. In thestep 6606, information related only to (e.g., by spatial/temporalproximity) the detected word/phrase/entity is fact checked. In someembodiments, the order of the steps is modified. In some embodiments,more or fewer steps are implemented.

In some embodiments, initially a single fact check monitors an entity(e.g., a commentator, a show, a network), but if the number ofmisleading comments, incorrect comments, and/or other characterizationsexceeds a threshold, additional fact checking systems monitor the entityusing different criteria for fact checking (e.g., different sources). Insome embodiments, exceeding the threshold results in the fact checkingsystem sending a notification to a group, agency, or anotherorganization. With additional monitoring and fact checking, it is morelikely that if one fact checking system does not catch a misleadingcomment, other fact checking systems will. The additional fact checkingsystems are able to parse the monitored information differently, comparethe information with different sources and/or indicate the results ofthe comparisons differently. In some embodiments, the multiple factchecking systems provide a single result, and in some embodiments,multiple results are presented. In an example, if a network continues toperpetuate falsehoods, and exceeds a first threshold, and then a secondthreshold, and then a third threshold, a fourth fact checkingsystem/implementation is used which provides a user supplementalinformation such as comparable networks that have a better accuracyrating. In some embodiments, one additional fact checkingsystem/implementation is utilized after each threshold is exceeded. Insome embodiments, the number of additional fact checkingsystems/implementations increases exponentially (e.g., 2, 4, 16, 32)after each threshold is exceeded.

In some embodiments, similar to described above, multiple thresholds areimplemented for each entity where the thresholds change the effect ofthe fact check result. For example, for the first five misleadingcomments (or biased comments, and/or any other characterization) acommentator provides, the fact checking system indicates “misleading”(or other characterization) for each comment. After the fifth misleadingcomment (fifth being the first threshold), a message that thecommentator appears to be biased is displayed. After the tenthmisleading comment (tenth being the second threshold), a suggestion tochange the channel is displayed with a suggestion of other channels thatare more factually accurate. The thresholds are able to be based on aper show basis, per day/week/month/year basis, starting from 0 and notresetting, or any other basis. In some embodiments, the message does notchange after each threshold, but the presentation of the messagechanges. For example, the message gets bigger after each threshold, orsound effects are applied and the sound gets louder, or the message ispresented in 3-D after a threshold is exceeded. Any other effectdescribed herein is able to be applied after any threshold is exceeded.In some embodiments, both the message changes and the presentation ofthe message changes.

FIG. 67 illustrates a flowchart of a method of implementing factchecking using multiple thresholds according to some embodiments. In thestep 6700, information is monitored. In the step 6702, the informationis processed. In the step 6704, the information is fact checked. In thestep 6706, a number of inaccuracies (or other characterization such asbias) of the information is computed (e.g., each time an inaccuracy isdetected, a counter increases). In the step 6708, the number ofinaccuracies is compared with a threshold. If the number is not abovethe threshold, then a first message (e.g., “misleading”) is presented ordisplayed, in the step 6710. If the number is above the threshold, thena second message (e.g., “commentator is biased”) is presented ordisplayed, in the step 6712. In some embodiments, additional thresholdsare implemented, and if the number is above the additional thresholds,additional messages and/or actions are implemented (e.g., suggesting achannel change). In some embodiments, the order of the steps ismodified. In some embodiments, more or fewer steps are implemented.

In some embodiments, information displayed as a result of a fact checkincludes a step-by-step process of why the fact checked information iscorrect, incorrect, misleading, and/or any other characterization.

As described herein, in some embodiments, email is fact checked. In someembodiments, an input implementation (e.g., command button) is includedwith/on a web page, web browser, or any application, such that when auser affects the input implementation, the email is fact checked. Forexample, a web page for sending/receiving email includes a button tofact check selected email or all email. The button is able to be usedbefore the email is sent, before a received email is opened, after anemail is opened, or any other time. In some embodiments, the content ofthe email is able to be selected by a user, and only the selectedcontent is fact checked after the user presses the fact check button. Insome embodiments, all or some email is fact checked in the cloud beforebeing received at a user's inbox. In some embodiments, a user is able tospecify types of email (e.g., only political emails) and/or email byspecified senders to be fact checked in the cloud. In some embodiments,a column or other area of an email inbox display indicates a fact checkresult for each email. For example, next to each email subject, an icon,text, number rating, and/or any other indication is displayed.Furthering the example, an email that is extremely factually inaccuratebased on a fact check receives a “1” next to the subject, and afactually accurate email receives a “10” next to the subject. In anotherimplementation, the number indicates the number of factually accurateand/or misleading content in the email. In some embodiments, a folder isimplemented with the email system similar to a spam email but for factchecked emails that have a factual accuracy below a threshold. In someembodiments, the content within the email is modified based on factchecking results. For example, factually inaccurate and/or misleadinginformation is highlighted, faded, stricken through, and/or any othereffect is applied. In some embodiments, emails are color-coded in auser's inbox, outbox, and/or any other folder based on the factualaccuracy of the email content. For example, email subjects, email tabs,or any other email descriptors/labels are color-coded. Furthering theexample, an email that is found to be factually accurate is color-codedgreen, an email that is found to be somewhat factually accurate (below afirst threshold) is color-coded yellow, and an email that is found to befactually inaccurate (below a second threshold) is color-coded red. Asdescribed herein, the fact checking and color coding is able to occurbefore the user opens the email, thus assisting the user in determiningwhich email to read and which to ignore. In some embodiments, statisticsare collected based on the fact checking of the emails, and thestatistics are able to be associated with a sender's email addressand/or other identifying information. For example, if the majority ofthe emails from sender-x are factually inaccurate, this information isable to be used in filtering emails as spam or factually inaccurate, forlabeling emails, and/or for providing users with additional informationabout the emails/senders. In some embodiments, selective fact checkingis implemented as described herein. Similarly, the selective factchecking is able to be implemented based on the type of email, thecontent of the email, the subject of the email, the sender of the email,and/or whether there is an attachment with the email. For example, aftera sender's emails have exceeded a threshold for the number of factuallyinaccurate emails, every additional email from that sender is factchecked. In another example, when political terms or phrases aredetected in an email (e.g., as determined using a database), the emailis fact checked. In another example, if the subject of the email isfactually inaccurate, the content of the email is fact checked, but ifthe subject of the email is factually accurate, the content of the emailis not fact checked. Any selectivity of fact checking emails is able tobe implemented. In some embodiments, when an email, tweet, and/or anyother communication is determined to have factually inaccurateinformation and/or misleading information (or factuallyinaccurate/misleading information exceeding a threshold), an email orother communication is automatically generated and/or automatically sentto the sender of the communication. The communication sent in responseis able to include corrections to the factually inaccurate or misleadinginformation, highlighting of questionable and/or biased information, anotification to the sender that he sent spam, and/or any otherinformation. In some embodiments, the communication sent in responsegoes to the sender as well as any other recipients of the communication,and/or any other senders of the communication. In some embodiments, thecommunication sent in response indicates a countdown/warning. Forexample, after the first email is determined to be spam based on theamount of factually inaccurate content in the email, a warning email issent to the sender that “this is your first strike, and if you receivetwo more, your email address will be added to the spam filter forfiltering.” Then, if three (or any specified number) emails that aredetermined to be spam based on factual inaccuracies are received fromthe sender, that email address is added to the spam filter. In someembodiments, when an email determined to be spam based on factualinaccuracies is received, a link and/or advertisement is sent to thesender to acquire a fact checking system. In some embodiments, if asender has a number of strikes against him for spam above a threshold,the sender is required to fact check (e.g., send an email to a factchecking system or utilize an automatic fact check system) before theuser is able to send the email. In some embodiments, the email sent bythe sender and the fact check of the email are sent to other contacts ofthe sender and/or originator of the email. For example, using socialnetwork information such as Facebook® contacts and/or a user's addressbook, the email and fact check result are sent to others to convince theuser to stop sending misinformation. The implementations describedherein related to email are able to be applied to any communicationincluding, but not limited to social media, text messages, and/orinstant messages.

FIG. 68 illustrates a block diagram of various implementations of factchecking according to some embodiments.

In some embodiments, a hologram output 6800 is utilized to present thefact checking results. The hologram output displays the causalrelationships found within a comment including highlighting the strengthof a causal relationship. For example, strong causal relationships areshown brightly, while weak causal relationships are shown lightly and nocausal relationships are shown disconnected. In an opposite manner, weakor missing causal relationships are highlighted. For example, acommentator states, “gas prices are going through the roof because ofthis President.” Based on fact checking results, a hologram output showsone connection of gas prices to investor speculation, another connectionshows gas prices tied to global demand, and a highlighted connectionshows there is no or little evidence of the President's policies causingan increase in gas prices. The hologram output is able to be anyrepresentation, for example, pillars, where each pillar represents acomponent of an argument, and highlighted pillars represent incorrectcausal relationships. Furthering the pillars example, the pillars holdup a structure representing an argument, and if the causal relationshipsare weak or non-existent, then the pillars and structure are presentedas falling down. In some embodiments, the hologram output is interactivesuch that users are able to move/interact with the hologram usinggestures, voice and/or any other way. The interaction is able to bedetected using a motion sensing/detection mechanism or any othermechanism.

In some embodiments, a device's power supply 6802 is operatively coupledto a fact checking system. In some embodiments, when inaccurateinformation is determined, the power supply is wasted/drained or notcharged (e.g., decoupled), and when accurate information or a correctionis determined, a power source, generator or charger is activated toprovide new power to the power supply. The generator is able to be anytype of generator such as a solar power generator. For example, a mobiledevice includes a solar cell which is operatively decoupled wheninaccurate information is determined until accurate information isdetermined as described herein. And when operatively coupled, the solarcell recharges a battery of the device. In some embodiments, a devicescreen becomes brighter (up to a desired level) incrementally asaccurate information or a correction to misinformation is determined,and the screen becomes darker (until black or other desired level)incrementally as inaccurate or misleading information is determined.

In some embodiments, a fact checking device is coupled (e.g.,wirelessly) to a storage device 6804 (e.g., DVR, hard drive, cloudstorage), and when a fact check result is determined in information(e.g., factually inaccurate), the information segment associated withthe fact check result is automatically stored in the storage devicealong with the fact check result. In some embodiments, additionalinformation is stored such as a quantity of each type of fact checkresult or total fact check results within a program or segment. In someembodiments, the storage device performs the fact checking and storingof the information. For example, a parsed television program segment isdetected to have a factually inaccuracy, and the segment isautomatically stored on the storage device. In some embodiments, usersare able to select which type of fact check result (e.g., onlyinaccurate information) is used in automatically storing information. Insome embodiments, a menu is provided for searching for and playing therecorded information. The menu is able to be sorted based on factchecking characteristics. In some embodiments, the recorded informationis searchable based on fact checking characteristics. For example, auser searches for all misinformation. In another example, a usersearches for all of the misinformation with an importance of theinformation above a threshold. In another example, a user searches forinaccurate information with a significance/relevance above a threshold.In some embodiments, the recorded content is able to be shared viasocial media/networking. For example, only friends of a user with animportance rating for the environment of 8 or higher receive a factchecking result involving a video clip about global warming. In someembodiments, shows/programs/segments/other information are stored onlyif a quantity of fact check results with a negative characteristic(e.g., factually inaccurate and misleading) is not above a threshold.For example, a user selects to record a news analysis program, but onlyif the program's quantity of negative fact check results are not above athreshold. In some embodiments, the program is recorded and fact checkedwhile ongoing, and if the fact check results exceed the threshold, thenthe recording stops and the program is automatically deleted. In someembodiments, a combination of selective recording (e.g., keyworddetection) and the fact checking threshold are utilized in recordingshows. For example, the user inputs a key phrase “gun control,” and onlyTV shows or segments with that phrase detected and with negative factchecking results below a threshold are recorded.

In some embodiments, for radio content 6806 or other information, usinga slight delay of a broadcast, the information is automatically factchecked as described herein, and then when the broadcast occurs to anaudience, the voice is modified (or other effect is applied such asplaying background music) when incorrect, misleading, and/or anothercharacterization is determined. For example, a radio broadcast occurs,but the broadcast to the audience is delayed by 30 seconds (or anothertime amount), so that the delayed broadcast is able to be fact checked(to prevent cutting off a sentence), and when the radio broadcast ispresented to the audience, any determined characterization is altered toindicate the fact check result in real-time. Furthering the example, aspeaker's voice is altered to a higher pitch when an inaccurate commentis made by the speaker, and an echoing effect is applied when amisleading comment is made by the speaker. The modification of the voiceis able to occur in any manner, for example, a signal or code isembedded (e.g., in a stream) which is detected and triggers the start ofthe sound effect and ends when an ending signal/code is detected. Inanother example, the tempo of the speaker's voice is increased or slowedbased on the fact checking result.

In some embodiments, a sound effect is automatically applied immediatelyafter a characterization is determined in real-time. In someembodiments, a light flashes on the dashboard, or a screen on thedashboard is used to indicate a fact check result.

In some embodiments, olfactory radio fact checking 6808 is implementedwhere the fact checking system communicates with or using a vehicleventilation/heat/air conditioning (A/C) system in conjunction with amulti-scent device (e.g., similar to an air freshener) on a vent ormultiple air fresheners on separate vents, or positioned elsewhere inthe vehicle. When a fact checking result is determined, the vehicle A/Csystem is triggered to blow air to cause a specified scent to disperse.For example, when a misleading comment is detected, a rotten smell isemitted, but when valid comments are made, a flower smell or fresh airis emitted. In another example, a mobile device performs the factchecking and sends the result to a vehicle computer which is configuredto turn on/off the A/C system based on the fact checking result. In someembodiments, a similar implementation is performed without a vehicle(e.g., at home, a scented device with one or more scents is used inconjunction with a fact checking system). In some embodiments, thescented device is merely pluggable into outlets controlled by the factchecking system which turn on/off a desired outlet, or a smart scenteddevice is used to achieve the desired scent. Similarly, heat and coldare able to be used to indicate accuracy versus inaccuracy or othercharacterizations. For example, an electric heat/cold pad is triggeredbased on the fact checking result. In some embodiments, the pad is ableto be pressed for more information. In another example, a steam or smokemachine or similar device is utilized with the fact checking system, anda puff of steam is emitted to indicate a fact check result.

In some embodiments, game content 6810 is utilized with and/or affectedbased on fact checking results. In some embodiments, game content isoverlaid on a device such that a character of the game affects thecontent being fact checked. For example, Pac-man eats the factuallyinaccurate closed-captioned information displayed on a television. Theincorporation of the gaming content is able to be performed in anymanner such as incorporated within the signal or projected on thecontent to only appear to eat the information. Any other game content isable to be applied to any characterization of the information. Forexample, fighting game characters beat up misleading content, or aprincess hugs a correction of incorrect content.

In some embodiments, a fact check result is used as input to a separategame. The game receives the input and is configured to perform astandard game function based on the input. For example, when a factuallyinaccurate comment is determined, space invaders get one step closer tothe bottom of a screen, and if there are too many inaccurate commentsdetermined, the game ends. In another example, each time a misleadingcomment is determined, a bird is slingshot at a structure hurting a pigin the structure. In another example, a game of pong with the opponentsbeing truth and fiction is presented, and if an inaccurate statement isdetected, the blip is shown as passing by truth's paddle giving fictiona point.

In some embodiments, a user plays a game which is affected by factchecking results. In some embodiments, the game is able to be playedwithout the fact checking results, but the fact checking results addextra features. For example, each time an inaccurate comment isdetermined (e.g., by monitoring and fact checking broadcast informationseparate from the game), the player within the game loses a life, eachtime a misleading comment is determined the player loses power oranother effect, each time a correction is determined, the player gains alife, and when hyperbole is determined, the player gains energy. In someembodiments, a user loses points in a game when misinformation isdetermined. In another example, a user plays a handheld fighting gamewhich includes power lost as usual from being hit by the opponent, butthe handheld game also monitors and fact checks or receives factchecking information from a television, and when misinformation in thetelevision broadcast is detected, the user loses power as if being hit.

In some embodiments, smart jewelry 6812 (e.g., bracelet, necklace, ring,pin) is implemented capable of receiving an input such as a fact checkresult from another device (e.g., smart phone implementing fact checkingsystem) and producing an output based on the input. For example, abracelet is configured to wirelessly receive a fact check result (e.g.,000 indicates misleading, 001 indicates inaccurate, 010 indicates bias)which then causes a lighting component (e.g., LED) in the bracelet toturn on for a period of time or as directed to turn off by the factchecking system. Similarly, clothing (e.g., armband/shirt) is able toinclude light effects.

In some embodiments, a microchip 6814 or other device configured to beinserted within a user is used for fact checking and/or receiving factchecking results. The microchip is configured to be able to trigger aphysiological effect on the user such as a tingling sensation upondetermination of misinformation. The microchip is able to be usedseparately or in conjunction with another device. For example, a user'ssmart phone or television monitors, processes and fact checksinformation, and then sends fact check results to the microchip (with areceiver) which provides an effect to the user. The effect provided bymicrochip is able to be implemented in any manner, for example,configured with an electrical output to generate a tingling or warmingsensation in a user. In some embodiments, the microchip is configured tosend signals to a user's brain to indicate to the user information isincorrect or another characterization. In some embodiments, themicrochip is positioned in or near a user's nose (or other location) togenerate a sensation (e.g., specific odor) that is not actually there.

In some embodiments, fact checking results are indicated based oninformation about the user (e.g., age, sex, occupation, politicalaffiliation, and/or any other information about the user). For example,if a user is a farmer, when a fact check result of the comment, “globalwarming is a hoax” indicates false, additional content such as droughtswhich have or will affect the farmer's crops are indicated. In anotherexample, when a fact check result of the comment, “the President isgoing to take away all of our guns,” indicates false, a picture of theguns being targeted by new legislation is indicated, or a specific noteto the user states, “you own guns X and Z which are unaffected by theproposed legislation.” In another example, each user's device isconfigured for that user to provide an output to specific to the user.For instance, a same fact checking result is communicated from anotherdevice to user's televisions, and each user's television indicates theresults in a manner specific to the user. Furthering the example, alluser's watching Show Z receive a signal on their television thatCommentator A's comment was misleading, but teenager User J's televisionshows the misinformation exploding, and elderly User K's televisionpresents a clear explanation in large print of why the comment wasmisleading. The user's information is able to be acquired, known, andused in any manner such as based on social network information, providedinformation, stored information, recent purchases, visited web sites,and/or channels watched.

As described herein, a fact check source collection system is able to beimplemented. The collection system searches for, processes, organizes,and stores sources to be used for fact checking. In some embodiments,sources not to be used are discarded or listed to be ignored.

In some embodiments, a database or other structure is maintained andutilized to automatically indicate a commonly spun word or phrase andalso to indicate bias or a political position based on the word orphrase used. For example, the database contains the phrase “estate tax”which is the legal term, and an associated column includes the phrase“death tax” which is a conservative term. The associated words/phrasesare able to be stored as well as political classifications associatedwith each, and any other information (e.g., who coined the phrase or thefactual accuracy of the phrase). Detecting the word/phrase is also ableto be used in determining bias of the speaker. For example, a person whouses the phrase “death tax” is likely a libertarian or conservative andnot a liberal.

In some embodiments, a size or length of a fact check result is userselectable. For example, a user is able to select that he wants the factcheck result to only be or mainly be emoticons, acronyms, shorthand,words, phrases, sentences, or paragraphs to indicate a result.

As described herein, the fact checking system is able to be used in manyapplications such as real estate, plumbing, roofing, painting,electrical, landscaping, mechanics, pest control, tech support, cable,phone, daycare, tutoring, contractors, event planning, dry cleaning,caterers, accountants, veterinarian, healthcare, tailors, hair/nailsalons, fitness, security, masseuse, house cleaners, banking,restaurants, job placement, legal, engineering, art, media,entertainment, customer service, education/schools, government,marketing, nonprofit, retail/sales, writing, and/or any other services.For example, for real estate, fact checking is able to be used to factcheck prices and property information. For services, pricing, reviews,documentation, and/or any other information is able to be fact checked.Supplemental information is able to be provided for these applicationsas well.

Utilizing the fact checking system, method and device depends on theimplementation to some extent. In some implementations, a word processoruses fact checking to assist a user in preparing a document, atelevision broadcast uses fact checking to fact check what is said orshown to the viewers, and a mobile application, in some embodiments,uses fact checking to ensure a user provides factually correctinformation. The fact checking is able to be implemented without userintervention. For example, if a user is watching a news program, thefact checking is able to automatically occur and present the appropriateinformation. In some embodiments, users are able to disable the factchecking if desired. Similarly, if a user implements fact checking onhis word processor or mobile application, the fact checking occursautomatically. For a news company, the fact checking is also able to beimplemented automatically, so that once installed and/or configured, thenews company does not need take any additional steps to utilize the factchecking. In some embodiments, the news company is able to takeadditional steps such as adding sources. In some embodiments, newscompanies are able to disable the fact checking, and in someembodiments, news companies are not able to disable the fact checking toavoid tampering and manipulation of data. In some embodiments, one ormore aspects of the fact checking are performed manually.

In operation, the fact checking system, method and device enableinformation to be fact checked in real-time and automatically (e.g.,without user intervention). The monitoring, processing, fact checkingand indicating of status are each able to occur automatically, withoutuser intervention. Results of the fact checking are able to be presentednearly instantaneously, so that viewers of the information are able tobe sure they are receiving accurate and truthful information.Additionally, the fact checking is able to clarify meaning, tone,context and/or other elements of a comment to assist a user or viewer.By utilizing the speed and breadth of knowledge that comes withautomatic, computational fact checking, the shortcomings of human factchecking are greatly overcome. With instantaneous or nearlyinstantaneous fact checking, viewers will not be confused as to whatinformation is being fact checked since the results are postedinstantaneously or nearly instantaneously versus when a fact check isperformed by humans and the results are posted minutes later. The rapidfact checking provides a significant advantage over past data analysisimplementations. Any of the steps described herein are able to beimplemented automatically.

Examples of Implementation Configurations:

Although the monitoring, processing, fact checking and indicating areable to occur on any device and in any configuration, these are somespecific examples of implementation configurations. Monitoring,processing, fact checking and indicating all occur on a broadcaster'sdevices (or other emitters of information including, but not limited to,news stations, radio stations and newspapers). Monitoring, processingand fact checking occur on a broadcaster's devices, and indicatingoccurs on an end-user's device. Monitoring and processing occur on abroadcaster's devices, fact checking occurs on a broadcaster's devicesin conjunction with third-party devices, and indicating occurs on anend-user's device. Monitoring occurs on a broadcaster's devices,processing and indicating occur on an end-user's device, and factchecking occurs on third-party devices. Monitoring, processing, factchecking, and indicating all occur on third-party devices. Monitoring,processing, fact checking, and indicating all occur on an end-user'sdevice. These are only some examples; other implementations arepossible. Additionally, supplemental information is able to be monitoredfor, searched for, processed and/or indicated using any of theimplementations described herein.

Fact checking includes checking the factual accuracy and/or correctnessof information. The type of fact checking is able to be any form of factchecking such as checking historical correctness/accuracy, grammaticalcorrectness/accuracy, geographical correctness/accuracy, mathematicalcorrectness/accuracy, scientific correctness/accuracy, literarycorrectness/accuracy, objective correctness/accuracy, subjectivecorrectness/accuracy, and/or any other correctness/accuracy. Another wayof viewing fact checking includes determining the correctness of astatement of objective reality or an assertion of objective reality. Yetanother way of viewing fact checking includes determining whether astatement, segment or phrase is true or false.

Although some implementations and/or embodiments have been describedrelated to specific implementations and/or embodiments, and someaspects/elements/steps of some implementations and/or embodiments havebeen described related to specific implementations and/or embodiments,any of the aspects/elements/steps, implementations and/or embodimentsare applicable to other aspects/elements/steps, implementations and/orembodiments described herein.

The present invention has been described in terms of specificembodiments incorporating details to facilitate the understanding ofprinciples of construction and operation of the invention. Suchreference herein to specific embodiments and details thereof is notintended to limit the scope of the claims appended hereto. It will bereadily apparent to one skilled in the art that other variousmodifications may be made in the embodiment chosen for illustrationwithout departing from the spirit and scope of the invention as definedby the claims.

What is claimed is:
 1. A computerized method comprising: automaticallydetecting, during access of media by a user, candidate information abouta candidate indicated in the media, the candidate information comprisingautomatic identification of the candidate and at least a first dataassociated with the candidate in the media; automatically processing thecandidate information to determine a particular topic corresponding tothe first data; automatically generating supplemental information basedon the candidate information that has been processed; automaticallypresenting, during access of the media by the user, the supplementalinformation about the candidate, the supplemental information comprisingone or more second data relating to the particular topic that ispreviously associated with the candidate; wherein the method isperformed by one or more computing devices.
 2. The method of claim 1,wherein processing comprises classifying the candidate information. 3.The method of claim 1, further comprising fact checking the candidateinformation by comparing the processed candidate information withinformation from a source, and the supplemental information comprises aresult of the fact checking.
 4. The method of claim 1, furthercomprising searching for the supplemental information.
 5. The method ofclaim 1, wherein the media comprises a political advertisement.
 6. Themethod of claim 1, wherein detecting includes at least one of voicerecognition, face recognition, and name recognition.
 7. The method ofclaim 1, wherein detecting includes detecting an entity associated withthe candidate.
 8. The method of claim 1, wherein the supplementalinformation comprises a campaign contribution implementation enabling auser to contribute to a campaign of the candidate.
 9. The method ofclaim 1, wherein the supplemental information comprises a single clickcampaign contribution implementation enabling a user to contribute to acampaign of the candidate.
 10. The method of claim 1, wherein thesupplemental information includes a list of positions of the candidateon issues in a ranked order.
 11. The method of claim 1, wherein thesupplemental information comprises statistics related to the candidate.12. The method of claim 1, wherein the media is presented on the device,and the supplemental information is presented on a second device that isdifferent than the device.
 13. The method of claim 1, wherein the mediaand the supplemental information are presented on the device.
 14. Themethod of claim 1, wherein the supplemental information is based on thecandidate and a detected keyword in the media.
 15. The method of claim1, wherein the supplemental information is based on the candidate andthe user's political classification.
 16. The method of claim 1, whereinthe supplemental information is based on the candidate and userpreferences.
 17. The method of claim 1, wherein the media comprises anadvertisement, and the supplemental information comprises an accuracyrating of the advertisement.
 18. The method of claim 1, wherein themedia includes a candidate comment, and further comprising classifyingand storing the candidate comment in a classification.
 19. A methodprogrammed in a non-transitory memory of a device, the methodcomprising: automatically detecting, during access of a media by a user,candidate information about a political candidate included in the media,the candidate information comprising automatic identification of thepolitical candidate using a face recognition technique and at least afirst data associated with the political candidate in the media;automatically processing the candidate information including convertingthe candidate information into searchable information and determining aparticular topic corresponding to the first data; automatically factchecking the searchable information by comparing the searchableinformation with information included in a source; automaticallypresenting, during access of the media by the user, a result of thecomparison of the searchable information and the information included inthe source and supplemental information about the political candidate,the supplemental information comprising one or more second data relatingto the particular topic that is previously associated with the politicalcandidate.
 20. A device comprising: a non-transitory memory for storingan application for automatically performing the following steps:detecting in a media being viewed by a user, an identity of a politicalcandidate and at least a first data associated with the politicalcandidate in the media; determining supplemental information based onthe identity of the political candidate and a particular topiccorresponding to the first data; presenting, during viewing of the mediaby the user, the supplemental information about the political candidate,the supplemental information comprising one or more second data relatingto the particular topic that is previously associated with the politicalcandidate; a processor for processing the application.